2024

• Chao, W., Duan, F., Guo, Y., & Wang, G. (2024). MaskBlur: Spatial and Angular Data Augmentation for Light Field Image Super-Resolution. IEEE Transactions on Multimedia, vol.26, pdf. code.

• Xu, W., Long, C., Nie, Y., & Wang, G. (2024). Disentangled Representation Learning for Controllable Person Image Generation. IEEE Transactions on Multimedia, vol.25, pdf. code.

• Chao, W., Duan, F., Wang, X., Wang, Y., & Wang, G. (2024). OccCasNet: Occlusion-aware Cascade Cost Volume for Light Field Depth Estimation. IEEE Transactions on Computational Imaging, vol.26, pdf. code.

• Zhang, H., Gao, X., Wang, Z., & Wang, G. (2024). Guest Editorial of the Special Section on Neural Computing-Driven Artificial Intelligence for Consumer Electronics. IEEE Transactions on Consumer Electronics, vol.70, pdf.

• Zhang, T., Xu, W., Luo, B., & Wang, G. (2024). Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets. Neurocomputing, vol.614, pdf. code.

• Han, G., Song, C., Wang, S., Wang, H., Chen, E., & Wang, G. (2024). Occluded Human Pose Estimation based on Limb Joint Augmentation . Neural Computing and Applications, vol.36, pdf. code.

• Li, K., Zhang, T., Zhong, C., Zhang, Z., & Wang, G. (2024). Robust 3D Point Clouds Classification based on Declarative Defenders . Neural Computing and Applications, vol.36, pdf. code.

• Alapati, R., Renslo, B., Jackson, L., Moradi, H., et al. (2024). Predicting Therapeutic Response to Hypoglossal Nerve Stimulation Using Deep Learning. Laryngoscope, vol.134, pdf.

• Rahman, R., Indris, C., Bramesfeld, G., Zhang, T., Li, K., McCornack, B., et al. (2024). A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields. Journal of Imaging, 10(5), pdf. code.

• Patel, K., Li, F., & Wang, G. (2024). Multi-Layer Dense Attention Decoder for Polyp Segmentation.. International Conference on Biomedical Engineering and Technology (ICBET). pdf, code.

• Rahman, R., Chowdhury, M., Tang, Y., Gao, H., Yin, G., & Wang, G. (2024). Kitchen Food Waste Image Segmentation and Classification for Compost Nutrients Estimation. International Conference on Electronics Technology (ICET). pdf.

• Vyas, T., Chowdhury, M., Xiao, X., Claeys, M., Ong, G., & Wang, G. (2024). Predicting Mitral Valve mTEER Surgery Outcomes Using Machine Learning and Deep Learning Techniques. International Conference on Mathematics and Artificial Intelligence (ICMAI). pdf.

• Chowdhury, M., Vyas, T., Alapati, R., Bur, A., & Wang, G. (2024). Assessing Patient Eligibility for Inspire Therapy through Machine Learning and Deep Learning Models. 16th International Conference on Bioinformatics and Biomedical Technology (ICBBT). pdf.

• Sepahvand, S., Wang, G., Janabi-Sharifi, F. (2024). Image-to-Joint Inverse Kinematic of a Supportive Continuum Arm Using Deep Learning. The 21st Conference on Robots and Vision (CRV). pdf.

• Amiri, N., Wang, G., Janabi-Sharifi, F. (2024). Keypoint Detection Technique for Image-Based Visual Servoing of Manipulators. IEEE International Conference on Automation Science and Engineering (CASE). pdf.

• Wang, S., Zhang, Z., Yan, H., Xu, M., Wang, G. (2024). Mix-Domain Contrastive Learning for Unpaired H&E-to-IHC Stain Translation. IEEE International Conference on Image Processing (ICIP). pdf.

• Chen, X., Liu, J., Wang, Y., Brand, M., Wang, G., Koike-Akino, T. (2024). SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models. CVPR 2024 Workshops. pdf.

• Chen, X., Liu, J., Wang, Y., Brand, M., Wang, G., Koike-Akino, T. (2024). SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules. arXiv preprint arXiv:2403.11887. pdf.

• Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T. (2024). SuperLoRA: Parameter-Efficient Unified Adaptation of Large Foundation Models. The 35th British Machine Vision Conference (BMVC). pdf.

• Wang, Y., Liang, Z., Chen, Q., et al. (2024). NTIRE 2024 challenge on light field image super-resolution: Methods and results. CVPR 2024 Workshops. pdf.

• Li, K., (2024). Accurate and Robust Object Detection and Classification Based on Deep Neural Networks. Ph.D. Dissertation, January. 2024

• Patel K., (2024). Image Classification and Segmentation based on Enhanced CNN and Transformer Networks. Ph.D. Dissertation, March. 2024

• Chen X., (2024). Toward Efficient Deep Learning for Computer Vision Applications. Ph.D. Dissertation, April, 2024

2023

• Xiao, X., Hu, Q., & Wang, G. (2023). Edge-aware Multi-task Network for Integrating Quantification Segmentation and Uncertainty Prediction of Liver Tumor on Multi-modality Non-contrast MRI. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2023 (early acceptance 14%) pdf.

• Chao, W., Wang, X., Wang, Y., Wang, G., Duan F. (2023). Learning Sub-Pixel Disparity Distribution for Light Field Depth Estimation. IEEE Transactions on Computational Imaging, vol.10, pdf. code.

• Bur, A., Zhang, T., Chen, X., Kavookjian, H., ..., & Wang, G. (2023). Interpretable Computer Vision for Localization and Classification of Structural Laryngeal Lesions using Digital Flexible Laryngoscopic Images. Otolaryngology – Head and Neck Surgery. pdf.

• Zhang, T., Li, K., Chen, X., Zhong, C., Luo, B., Grijalva, I., McCornack, B., Flippo, D., Sharda, A., & Wang, G. (2023). Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models. Scientific Reports, Springer Nature, pdf.

• Zhang, T., Bur, A., Kraft, S., Kavookjian, H., Renslo, B., Chen, X., Luo, B., & Wang, G. (2023). Gender, Smoking History, and Age Prediction from Laryngeal Images. J. Imaging. pdf.

• Zhang, Z., Li, K., & Wang, G. (2023). Robust Structured Declarative Classifiers for Point Clouds. Annual Review of Artificial Intelligence pdf.

• Gowravaram, S., Chao, H., Lin, Z., Parsons, S., Zhao, T., Xin, M., Hu, X., Tian, P., Flanagan, H., & Wang, G. (2023). Prescribed grass fire mapping and rate of spread measurement using NIR images from a small fixed-wing UAS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. pdf.

• Claeys, M., Vyas, T., Chowdhury, M., Prud'Homme, P., et al. (2023). Artificial Intelligence to Predict Optimal Procedural Outcome After Mitral Transcatheter Edge-to-Edge Repair. Journal of the American College of Cardiology, pdf.

• Cheppally, H., Sharda, A., & Wang, G. (2023). Seed localization system suite with CNNs for seed spacing estimation, population estimation and doubles identification. Smart Agricultural Technology, Elsevier. pdf.

• Chao, W., Duan, F., Wang, X., Wang, Y., & Wang, G. (2023). OccCasNet: Occlusion-aware Cascade Cost Volume for Light Field Depth Estimation. arXiv preprint arXiv:2305.17710, 2023. pdf. code.

• Chen, X., Hu, Q., Li, K., Zhong, C., & Wang, G. (2023). Accumulated Attention Matters in Vision Transformers on Small Datasets. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023. pdf. code.

• Chen, X., Zhen, R. Li, S., Li, X., & Wang, G. (2023). MOFA: A Model Simplification Roadmap for Image Restoration on Mobile Devices. ICCV 2023 Workshops. pdf. code.

• Zhang, T., Li, K., Chen, X., Zhong, C., Luo, B., Grijalva, I., McCornack, B., Flippo, D., Sharda, A., & Wang, G. (2023). A New Dataset and Comparative Study for Aphid Cluster Detection. AAAI 2023 Workshop, pdf. code.

• Rahman, R., Indris, C., Zhang, T., Li, K., McCornack, B., Flippo, D., Sharda, A., & Wang, G. (2023). On the Real-Time Semantic Segmentation of Aphid Clusters in the Wild. CVPR 2023 Workshop, pdf. code.

• Wang, Y., Zhu, H., & Wang, G. (2023). PST-Net: Point Cloud Completion Network Based on Local Geometric Feature Reuse and Neighboring Recovery with Taylor Approximation. International Joint Conference on Neural Networks (IJCNN), pdf. code.

• Chao, W., Duan, F., Wang, X., Wang, Y., & Wang, G. (2023). LFSRDiff: Light Field Image Super-Resolution via Diffusion Models. arXiv preprint arXiv:2311.16517, pdf. code.

• Wang, G., Rahman, R., Zhang, T., Li, K., McCornack, B., Flippo, D., Sharda, A. (2023). A New Dataset and Comparative Study for Aphid Cluster Detection. International Conference on Artificial Intelligence, Automation and Algorithms (AI2A) 2023, Extended abstract.

• Wang, Y., Wang, L., Liang, Z., et al. (2023). NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results. CVPR 2023 Workshop, pdf.

• Sheng, H., Liu, Y. Wu, G., et al. (2023). LFNAT 2023 challenge on light field depth estimation: Methods and results. CVPR 2023 Workshop, pdf. Our model SF-Net won third place at the Light Field Depth Estimation Challenge.

2022

• Li, K., Zhang, Z., Zhong, C., & Wang, G. (2022). Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. pdf. source code.

• Ma, W., Tu, X., Luo, B., & Wang, G. (2022). Semantic clustering based deduction learning for image recognition and classification. Pattern Recognition, vol.124, pdf. code. (impact factor: 7.74)

• Yang, Y., Zhang, T., Li, G., Kim, T., & Wang, G. (2022). An Unsupervised Domain Adaptation Model based on Dual-module Adversarial Training. Neurocomputing, pdf. code. (impact factor: 5.719)

• Sajid, U., & Wang, G. (2022). Towards more effective PRM-based crowd counting via a multi-resolution fusion and attention network. Neurocomputing, pdf, vol.474, 2022. (impact factor: 5.719)

• Patel, K., & Wang, G. (2022). A discriminative channel diversification network for image classification. Pattern Recognition Letters, vol.153. pdf. code. (impact factor: 3.756)

• Zhang, T., Luo, B., Sharda, A., & Wang, G. (2022). Dynamic label assignment for object detection by combining predicted IoUs and anchor IoUs. Journal of Imaging, vol.8(7). pdf. (impact factor: 3.806)

• Wilson, B., Tucci, D., Moses, D., et al. (2022). Harnessing the power of artifcial intelligence in Otolaryngology and the communication sciences. Journal of the Association for Research in Otolaryngology (JARO), vol.23, 1-31. Springer Nature. pdf. (impact factor: 3.057)

• Patel, K., Bur, A., Li, F., & Wang, G. (2022). Aggregating global features into local vision Transformer. The 26th International Conference on Pattern Recognition (ICPR). pdf. code. (Best Student Paper Award)

• Yang, Y., Kim, T., & Wang, G. (2022). Multiple classifiers Based maximum classifier siscrepancy for unsupervised domain adaptation. The 19th Conference on Robots and Vision (CRV 2022), pdf. code.

• Patel, K., Li, F., & Wang, G. (2022). FuzzyNet: A Fuzzy Attention Module for Polyp Segmentation. NeurIPS 2022 Workshop. pdf. code.

• Chen, X., Qin, Y., Bur, A., Zhong, C., & Wang, G. (2022). Explicitly Increasing Input Information Density for Vision Transformers on Small Datasets. NeurIPS 2022 Workshop. pdf. code.

• Sui, Y., Wang, G., Zhang, L. (2022). In defense of subspace tracker: Orthogonal embedding for visual tracking. https://doi.org/10.48550/arXiv.2204.07927, pdf.

• Ma, W., Zhang, T., & Wang, G. (2022). Miti-DETR: Object detection based on transformers with mitigatory self-attention convergence. AAAI 2022 Workshop, pdf. code.

• Chen, X., Qin, Y., Xu, W., Bur, A., Zhong, C., & Wang, G. (2022). Improving vision transformers on small datasets by increasing input information density in frequency domain. CVPR 2022 Workshop, pdf.

2021

• Xu, W., Long, C., Wang, R., & Wang, G. (2021). DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer. IEEE/CVF International Conference on Computer Vision (ICCV), oral (acceptance rate: 3%). pdf. code.

• Xu, W., & Wang, G. (2021). A Domain Gap Aware Generative Adversarial Network for Multi-domain Image Translation. IEEE Trans. on Image Processing, 2021. (impact factor: 10.856)

• Xia, S., Xu, S., Wang, R., Li, J., & Wang, G. (2021). Building instance mapping from ALS point clouds aided by polygonal maps. IEEE Trans. on Geoscience and Remote Sensing, https://doi.org/10.1109/TGRS.2021.3087159. 2021. (impact factor: 5.855)

• Cen, F., Zhao, X., Li, W., & Wang, G. (2021). Deep feature augmentation for occluded image classification. Pattern Recognition, https://doi.org/10.1016/j.patcog.2020.107737. 2021. (impact factor: 7.74)

• He, L., Lu, J., Wang, G., Song, S., & Zhou, J. (2021). SOSD-Net: Joint semantic object segmentation and depth estimation from monocular images. Neurocomputing, 440, 251-263. 2021. (impact factor: 4.438)

• Spiesman, B. J., Gratton, C., Hatfield, R. G., Hsu, W. H., Jepsen, S., McCornack, B., ... & Wang, G. (2021). Assessing the potential for deep learning and computer vision to identify bumble bee species from images. Scientific Reports, 11(1), 1-10, 2021. (impact factor: 3.998)

• Mo, X., Sajid, U., & Wang, G. (2021). Stereo frustums: A siamese pipeline for 3D object detection, Journal of Intelligent & Robotic Systems. 2021. (impact factor: 2.259)

• Li, K., Fathan, M. I., Patel, K., Zhang, T., Zhong, C., Bansal, A., ... & Wang, G. (2021). Colonoscopy Polyp Detection and Classification: Dataset Creation and Comparative Evaluations. Plos ONE, 2021. dataset

• Woodruff, T., Askari,, I., Wang, G., Fang, H. (2021). Model Predictive Control of Nonlinear Latent Force Models: A Scenario-Based Approach. IEEE International Conference on Robotics and Automation (ICRA), 2021.

• Sajid, U., Chen, X., Sajid, H., Kim,, T., & Wang, G. (2021). Audio-Visual Transformer Based Crowd Counting. IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), oral. code. 2021.

• Sajid, U., Ma, W., & Wang, G. (2021). Multi-resolution fusion and multi-scale input priors based crowd counting. the 25th International Conference on Pattern Recognition (ICPR), 2021.

• Sajid, U., Chow, M., Zhang, J., Kim, T., & Wang, G. (2021). Parallel Scale-wise Attention Network for Effective Scene Text Recognition. The International Joint Conference on Neural Networks (IJCNN), oral, 2021.

• Chen, X., & Wang, G. (2021). Few-Shot Learning by Integrating Spatial and Frequency Representation. The Conference on Robots and Vision (CRV), oral, 2021. code

• Patel, K., Bur, A. M., & Wang, G. (2021). Enhanced U-Net: A Feature Enhancement Network for Polyp Segmentation. The Conference on Robots and Vision (CRV), 2021. code

• Li, K., Wang, N. Y., Yang, Y., & Wang, G. (2021). SGNet: A Super-class Guided Network for Image Classification and Object Detection. The Conference on Robots and Vision (CRV), 2021. code

• Gajurel, K., zhong, C., & Wang, G. (2021). A Fine-Grained Visual Attention Approach for Fingerspelling Recognition in the Wild. IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021. code

• Wu, Y., Zhang, Z., & Wang, G. (2021. Branch-and-Pruning Optimization Towards Global Optimality in Deep Learning. arXiv preprint arXiv:2104.01730, 2021.

• McClannahan, B., Zhong, C., & Wang, G. (2021). Classification of Long Noncoding RNA Elements Using Deep Convolutional Neural Networks and Siamese Networks. arXiv preprint arXiv:2102.05582, 2021.

• Zhang, T., Ma, W., & Wang, G. (2021). Six-channel Image Representation for Cross-domain Object Detection. The 11th International Conference on Image and Graphics (ICIG), 2021.

• Zhang, T., Zhang, X., Yang, Y., Wang, Z., & Wang, G. (2020). Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter. arXiv preprint arXiv:2012.09393, 2020. dataset

• Yang, Y., Kim, T., & Wang, G. (2021). Multiple Classifiers Based Maximum Classifier Discrepancy for Unsupervised Domain Adaptation. arXiv preprint arXiv:2108.00610, pdf. code.

• Ma, W., (2021). Object Detection and Classification based on Hierarchical Semantic Features and Deep Neural Networks. Ph.D. Dissertation, July. 2021

• Sajid, U., (2021). Effective Uni-Modal to Multi-Modal Crowd Estimation based on Deep Neural Networks. Ph.D. Dissertation, December. 2021

2020

• Sajid, U., Sajid, H., Wang, H., & Wang, G. (2020). ZoomCount: A zooming mechanism for crowd counting in static images. IEEE Transactions on Circuits and Systems for Video Technology. DOI: 10.1109/TCSVT.2020.2978717. 2020. (impact factor: 4.133)

• Sangha, H.S., Sharda, A, Koch, L., Wang, G., Prabhakar, P. (2020). Impact of camera focal length and sUAS flying altitude on spatial crop canopy temperature evaluation.Computers and Electronics in Agriculture. vol. 172 (impact factor: 3.858)

• Ma, W., Wu, Y, Cen, F., & Wang, G. (2020). MDFN: Multi-scale deep feature learning network for object detection. Pattern Recognition. vol.100. (impact factor: 7.196)

• Xu, W., Wu, Y, Ma, W., & Wang, G. (2020). Adaptively denoising proposal collection for weakly supervised object localization. Neural Processing Letters, doi.org/10.1007/s11063-019-10124-7. 2020. (impact factor: 2.891)

• Ma, W., Li, K., & Wang, G. (2020). Location-aware box reasoning for anchor-based single-shot object detection. IEEE Access, 8, 129300-129309. 2020. (impact factor: 4.098)

• Patel, K., Li, K., Tao, K., Wang, Q., Bansal, A., Rastogi, A., & Wang, G. (2020). A comparative study on polyp classification using convolutional neural networks. PloS one, 15(7), https://doi.org/10.1371/journal.pone.0236452. (impact factor: 2.870)

• Ma, W., Yu, M., Li, K., & Wang, G. (2020). Why layer-wise learning is hard to scale-up and a possible solution via accelerated downsampling. IEEE International Conference on Tools with Artificial Intelligence (ICTAI). (Acceptance rate: 25%)

• Sajid, U., & Wang, G. (2020). Plug-and-play rescaling based crowd counting in static images. IEEE Winter Conference on Applications of Computer Vision (WACV). 2020

• Zhang, Z., Ma, W., Wu, Y., Wang, G., & Sullivan, A. (2020). Self-orthogonality module: A network architecture plug-in for learning orthogonal filters. IEEE Winter Conference on Applications of Computer Vision (WACV). 2020

• Zhang, Z., Xu, W., Wang, G., & Sullivan, A. (2020). Towards learning affine-invariant representations via data-efficient CNNs. IEEE Winter Conference on Applications of Computer Vision (WACV). 2020

• Li, H., Cai, H., & Wang, G. (2020). Improving high dynamic range image based light measurement, IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020.

• McClannahan, B., Patel, K., Sajid, U., Zhong, C., & Wang, G. (2020). Classification of noncoding RNA elements using deep convolutional neural networks. IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020.

• Zhang, X., Zhang, T., Yang, Y., Wang, Z., & Wang, G. (2020). Real-time golf ball detection and tracking based on convolutional neural networks. IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020. dataset

• Li, K., Wu, Y, Ma, W., Sajid, U., & Wang, G. (2020). Object detection with convolutional neural networks. Deep Learning in Computer Vision: Principles and Applications, ISBN 9781138544420. 2020.

• Zhang, T., Zhang, X., Yang, Y., Wang, Z., & Wang, G. (2020). Efficient golf ball detection and tracking based on convolutional neural networks and Kalman filter. arXiv:2012.09393, 2020.

2019

• Cen F., & Wang, G. (2019). Boosting occluded image classification via subspace decomposition based estimation of deep features. IEEE Transactions on Cybernetics, DOI:  10.1109/TCYB.2019.2931067. 2019. (impact factor: 10.387)

• Sui, Y., Zhang Z., Wang, G., Tang, Y., & Zhang, L., (2019). Exploiting the anisotropy of correlation filter learning for visual tracking. International Journal of Computer Vision, doi.org/10.1007/s11263-019-01156-6, 2019. (impact factor: 11.541)

• Sui, Y., Wang, G., & Zhang, L (2019). Joint correlation filtering for visual tracking. IEEE Transactions on Circuits and Systems for Video Technology, DOI: 10.1109/TCSVT.2018.2888573. 2019. (impact factor: 4.046)

• Sui, Y., Wang, G., & Zhang, L (2019). Sparse subspace clustering via low-rank structure propagation. Pattern Recognition. vol. 95, pp. 261-271. (impact factor: 5.898)

• Xu, W., Keshmiri, S., & Wang, G. (2019). Adversarially approximated autoencoder for image generation and manipulation. IEEE Transactions on Multimedia. DOI:  10.1109/TMM.2019.2898777 2019 (impact factor: 5.452)

• Xu, W., Keshmiri, S., & Wang, G. (2019).Stacked Wasserstein Autoencoder. Neurocomputing, pdf. (impact factor: 4.072)

• Xu, W., Keshmiri, S., & Wang, G. (2019). Toward learning a unified many-to-many mapping for diverse image translation. Pattern Recognition. vol. 93, pp. 570-580. (impact factor: 5.898)

• Cen F., & Wang, G. (2019). Dictionary representation of deep features for occlusion-robust face recognition. IEEE Access, DOI:  10.1109/ACCESS.2019.2901376, 2019. (impact factor: 4.098)

• Zhu, H., Yang, T., Yang, P., He, L., & Wang, G. (2019). 3D reconstruction for ultrasonic C-scan images of tissue-mimicking phantom based on an improved K-nearest neighbor filtering. Multimedia Tools and Applications,  doi:https://doi.org/10.1007/s11042-019-7686-1, 2019. (impact factor: 2.101)

• Sangha, H., Sharda, A., Koch, L., Wang, G., & Prabhakar, P. (2019). Impact of camera lens angle and sUAS flying altitude on spatial crop canopy temperature evaluation. Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV (SPIE vol. 11008), doi:https://doi.org/10.1117/12.2519378, 2019.

• Zhu, P., Wen, L., ..., Wang, G., et al. (2019). VisDrone-DET2018: The vision meets drone object detection in image challenge results. ECCV 2018 Workshops, Lecture Notes in Computer Science, (LNCS, volume 11133) pp. 437-468, 2019.

• Wu, Y., Zhang, Z., & Wang, G. (2019). Unsupervised deep feature transfer for low resolution image classification. International Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos, affiliated with ICCV 2019, 2019.

• Wu, Y., Marks, T., Cherian, A., Chen, S., Feng, C., Wang, G., & Sullivan, A. (2019). Unsupervised joint 3D object model learning and 6D pose estimation for depth-based instance segmentation. the 5th International Workshop on Recovering 6D Object Pose, affiliated with ICCV 2019, 2019.

• Wu, Y., (2019). Optimization for Training Deep Models and Deep Learning Based Point Cloud Analysis and Image Classification. Ph.D. Dissertation, Dec. 2019

• Xu, W., (2019). Image Cognition for Bio-inspired Navigation and Guidance of Autonomous System. Ph.D. Dissertation, Dec. 2019

2018

• Huo, J., Wu, J., Cao, J., & Wang, G. (2018). Supervoxel based method for multi-atlas segmentation of brain MR images. NeuroImage, vol.175, pp.201-214 2018. (impact factor: 5.812)

• He, L., Wang, G., & Hu, Z. (2018). Learning depth from single images with deep neural network embedding focal length,.IEEE Transactions on Image Processing, vol.27(9), pp. 4676 - 4689, 2018 (impact factor: 6.790)

• Sui, Y., Wang, G., Zhang, L. & Yang, M.X. (2018). Exploiting spatial-temporal locality of tracking via structured dictionary learning. IEEE Transactions on Image Processing, vol.27(3), pp.1282-1296, 2018. (impact factor: 6.790)

• Bharati, S., Wu, Y., Sui, Y., Padgett, C., & Wang, G. (2018). Real-time obstacle detection and tracking for sense-and-avoid mechanism in UAVs. IEEE Transactions on Intelligent Vehicles, DOI: 10.1109/TIV.2018.2804166, 2018.

• Bharati, S., Cen, F. Sharda, A., & Wang, G. (2018). RES-Q: Robust outlier detection algorithm for fundamental matrix estimation. IEEE Access,DOI:  10.1109/ACCESS.2018.2867915, 2018. (impact factor: 4.098)

• Zhu, H., Wen, X., Zhang, F., Wang, X., & Wang, G. (2018). Homography estimation based on order-preserving constraint and similarity measurement. IEEE Access,  DOI:  10.1109/ACCESS.2018.2837639, 2018. (impact factor: 4.098)

• Zhang,, Z., Wu, Y., & Wang, G. (2018). BPGrad: Towards global optimality in deep learning via branch and pruning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

• He, L., Miao, Y., & Wang, G. (2018). Spindle-Net: CNNs for monocular depth inference with dilation kernel method . the 24th International Conference on Pattern Recognition (ICPR), 2018.

• Ma, W., Wu, Y., Wang, Z., & Wang, G. (2018). MDCN: Multi-scale, deep inception convolutional neural networks for efficient object detection. the 24th International Conference on Pattern Recognition (ICPR), 2018.

• Mo, X., Tao, K., Wang, Q., & Wang, G. (2018). An efficient approach for polyps detection in endoscopic videos based on faster R-CNN . the 24th International Conference on Pattern Recognition (ICPR), 2018.

• Bharati, S., (2018). Vision Based Adaptive Obstacle Detection, Robust Tracking and 3D Reconstruction for Autonomous Unmanned Aerial Vehicles. Master's Thesis, Jan. 2018

2017

• Sui, Y., Wang, G., Zhang, L.(2017). Correlation filter learning toward peak strength for visual tracking. IEEE Transactions on Cybernetics, vol. 48 (4) pp.1290-1303. 2018. (impact factor: 10.387)

• Sui, Y., Tang, Y., Zhang, L.,Wang, G., (2017). Visual tracking via subspace learning: A discriminative approach. International Journal of Computer Vision, vol. 126 (5), pp.515-536, 2018. (impact factor: 11.541)

• Wu, Y., Sui, Y., & Wang, G. (2017). Vision-based real-time aerial object localization and tracking for UAV sensing system. IEEE Access,  vol.5, pp.23969-23978, 2017. (impact factor: 4.098) [project page with dataset and source code]

• Xu, W., Choi, D., & Wang, G. (2017). Direct visual-inertial odometry with semi-dense mapping. Computers & Electrical Engineering, Special Issue on Learning based Decision Making in Robotics, https://doi.org/10.1016/j.compeleceng.2018.02.002, 2017. (impact factor: 2.189)

• Wang, G. (2017). Robust structure and motion recovery based on augmented factorization. IEEE Access, vol.5(1): pp.18999–19011, 2017. (impact factor: 4.098)

• Yang, J., Wang, Y., Wang, G., & Li, M. (2017). Salient object detection based on global multi-scale superpixel contrast. IET Computer Vision, vol.11 (8) pp.710-716, 2017. (impact factor: 1.087)

• Yang, J., Yang, F., Wang, G., & Li, M. (2017). Multi-channel and multi-scale mid-level image representation for scene classification. Journal of Electronic Imaging. vol.26 (2), 2017. (impact factor: 1.061)

• Alshazly, H., Hassaballah, M., Ali, A., & Wang, G. (2017). An experimental evaluation of binary feature descriptors. International Conference on Advanced Intelligent Systems and Informatics (AISI). 2017.

2016

• Wu, F., Zhang, M., Wang, G., & Hu, Z. (2016). Triangulation and metric of lines based on geometric error. Computer Vision and Image Understanding, vol.145, pp.111-127, 2016. (impact factor: 2.498)

• He, L., Dong, Q., Wang, G., Hu, Z. (2016) Fast depth extraction from a single image, International Journal of Advanced Robotic Systems. vol.13, 2016. (impact factor: 1.223)

• Gao, J., Yang, J., Wang, G., & Li, M. (2016). A novel feature extraction method for scene recognition based on centered convolutional restricted Boltzmann machines. Neurocomputing, vol. 214: 708-717, 2016. (impact factor: 4.072)

• Yang, J., Zhang, J., Wang, G., & Li, M. (2016). Contour detection based discovery of mid-level discriminative patches for scene classification . International Journal of Advanced Robotic Systems. vol.13, 2016. (impact factor: 1.223)

• Sui, Y., Wang, G., Tang, Y., Zhang, L. (2016). Tracking completion, European Conference on Computer Vision (ECCV), 2016. (Acceptance rate: 26%) [poster]

• Sui, Y., Zhang, Z., Wang, G., Tang, Y., Zhang, L. (2016). Real-time visual tracking: promoting the robustness of correlation filter learning, European Conference on Computer Vision (ECCV), 2016. (Acceptance rate: 26%) [poster]

• Tian, Y., Sompalli, R., Wang, G., Luo, B. (2016). Textual ontology and visual features based search for a paleontology digital library, The 28th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2016. [oral]

• Bharati, S., Nandi, S., Wu, Y., Sui, Y., Wang, G. (2016). Fast and robust object tracking with adaptive detection, The 28th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2016. [project page with dataset and source code]

• Wang, G. (ed.). (2016). Recent Advances in Robotic Systems. InTech. ISBN: 978-953-51-2570-9, 2016

2015

• Yang, J., Zhang, S., Wang, G., & Li, M. (2015). Scene and place recognition using a hierarchical latent topic model. Neurocomputing.148: 578-586, 2015 (impact factor: 4.072)

• Wang, G. (2015). Robust Structure and motion factorization of non-rigid objects, Frontiers in Robotics and AI, 2015 (30) (invited)

• Wu, F., Zhang, M., Wang, G., & Hu, Z. (2015). Algebraic error based triangulation and metric of lines. PLoS ONE, 10(7) (impact factor: 3.234)

• Li, X., Wang, G., & Wu, J. (2015). Research on the fundamental principles and characteristics of correspondence functions. Mathematical Problems in Engineering, vol.2015 (impact factor: 1.145)

• Yang, J., Zhang, J., Wang, G., & Li, M. (2015). Semantic map building based on object detection for indoor navigation. International Journal of Advanced Robotic Systems. vol.12, 2015 (impact factor: 1.223)

• Mukherjee, D., Wu, J., Wang, G. (2015). A comparative experimental study of image feature detectors and descriptors. Machine Vision and Applications 26:443–466 (impact factor: 2.005)

• Huo, J., Wang, G., Wu, J., Thangarajah, A. (2015). Label fusion for multi-atlas segmentation based on majority voting. ICIAR 2015, Lecture Notes in Computer Science (LNCS) vol. 9164

• Zhang, M., Wang, G., Chao, H., Wu, F. (2015). Fast and robust algorithm for fundamental matrix estimation. ICIAR 2015, Lecture Notes in Computer Science (LNCS) vol. 9164

• Sarkar, S., Liu, J., Wang, G. (2015). Biometric analysis of human ear matching using scale and rotation invariant feature detectors. ICIAR 2015, Lecture Notes in Computer Science (LNCS) vol. 9164

• Liu J., Zheng, E., Wang, G. (2015). 3D Reconstruction from image sequence. In Proc. International Conference on Software, Multimedia and Communication Engineering (SMCE). 2015

2014

• Wang, G., Zelek, J., & Wu, J. (2013). Structure and Motion Factorization of Nonrigid Objects. In 3D Reconstruction: Methods, Applications and Challenges (18 pages). ISBN: 978-1-62948-265-1

• Wang, G., Zelek, J., Wu, J., & Bajcsy, R. (2013). Robust rank-4 affine factorization for structure from motion. In IEEE Workshop on the Applications of Computer Vision (WACV 2013) (pp. 180-185).

• Wang, G., Liu, J., & Zhang, H. (2013). Alternative weighted structure from motion under quasi-perspective projection model. In IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP).

• Wang, G., Zelek, J., & Wu, J. (2013). Robust structure from motion of nonrigid objects in the presence of outlying and missing data. In Canadian Conference on Computer and Robot Vision (CRV 2013).

• Zhao, W., Yang, J., Li, M., & Wang, G. (2014). Robust monocular SLAM using one 3D point. In 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE).

• Liu, J., Jin, M., Ma, R., Cai, G., & Wang, G. (2013). FPGA implementation method of compressed sensing. Instrument Technique and Sensor, 2013(10).

• Liu, J., Jin, M., Ma, R., Cai, G., & Wang, G. (2013). Wavelet sparsity based compressive sensing and reconstruction for mobile robot environmental vision. Journal of Nanchang University (Engineering & Technology), 35(3).

• Wang, G., (2014). Robust and Accurate Structure from Motion of Rigid and Nonrigid Objects. Ph.D. Dissertation, Aug. 2014

2012

• Wang, G., Zelek, J., & Wu, J. (2012). Structure and motion recovery based on spatial-and-temporal-weighted factorization. IEEE Trans. on Circuits and Systems for Video Technology (T-CSVT), 22(11), 1590-1603. , (impact factor: 3.599) (16 pages)

• Zhang, W., Wu, J., & Wang, G. (2012). Tracking and pairing vehicle headlight in night scenes. IEEE Trans. on Intelligent Transportation Systems (T-ITS), 13(1), 140-153. , (impact factor: 3.724) (14 pages)

• Wang, G., & Wu, J. (2011). Guide to Three-Dimensional Structure and Motion Factorization. Springer-Verlag. ISBN: 978-0-85729-045-8

• Wang, G., Zelek, J., & Wu, J. (2011). Spatial-and-temporal-weighted structure from motion. In Canadian Conference on Computer and Robot Vision (CRV 2011), (Best Robotics Paper Award)

2010

• Wang, G., & Wu, J. (2010). Quasi-perspective projection model: Theory and application to structure and motion factorization from uncalibrated image sequences. International Journal of Computer Vision (IJCV), 87(3), 213-234. , (impact factor: 8.222) (22 pages)

• Wang, G., & Wu, J. (2010). The quasi-perspective model: Geometric properties and 3D reconstruction. Pattern Recognition, 43(5), 1932-1942. , (impact factor: 4.582) (11 pages)

• Zhang, W., Wu, J., & Wang, G. (2010). An adaptive computational model for salient object detection. IEEE Trans. on Multimedia (T-MM), 12(4), 300-316. , (impact factor: 3.509) (16 pages)

• Mukherjee, D., Wang, G., & Wu, J. (2010). Stereo correspondence based on curvelet decomposition, support weights and disparity calibration. Optical Engineering, 49(4), 047202. , (impact factor: 1.082) (13 pages)

• Liu, J., Wu, X., Xia, J., & Wang, G. (2010). Visual navigation of a novel economical embedded multi-mode intelligent control system for powered wheelchair. In The Seventh International Symposium on Neural Networks (ISNN 2010).

• Liu, J., Zhang, H., Fan, B., & Wang, G. (2010). A novel economical multi-mode embedded intelligent control system for powered wheelchair. In International Conference on Computing, Control and Industrial Engineering (CCIE 2010).

• Mukherjee, D., Wang, G., & Wu, J. (2010). Stereo matching using curvelets and support weights. In International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010).

• Sun, G., Tian, Y., & Wang, G. (2010). Quasi-perspective structure factorization with missing data. In International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010).

• Wang, G., & Wu, J. (2010). Structure and motion Factorization of Nonrigid Objects under Full Perspective Projection. In 3D Imaging: Theory, Technology and Applications (pp. 26 pages). ISBN: 978-1-60876-885-1

• Wang, G., & Wu, J. (2010). Vanishing Points Based 3D Reconstruction of Structured Scenes. In 3D Imaging: Theory, Technology and Applications (24 pages). ISBN: 978-1-60876-885-1

• Wang, G., & Wu, J. (2009). Perspective 3D Euclidean reconstruction with varying camera parameters. IEEE Trans. on Circuits and Systems for Video Technology (T-CSVT), 19(12), 1793-1803. , (impact factor: 3.599) (11 pages)

• Zhang, W., Wu, J., & Wang, G. (2009). Image matching using enclosed region detector. Journal of Visual Communication and Image Representation, 21(4), 271-282. , impact factor: 1.342 (11 pages)

• Wang, G., Tsui, H., & Wu, J. (2009). What can we learn about the scene structure from three orthogonal vanishing points in images. Pattern Recognition Letters, 30(3), 192-202. , (impact factor: 2.164) (11 pages)

• Wang, G., & Wu, J. (2009). Two-view geometry and reconstruction under quasi-perspective projection. In Asian Conference on Computer Vision (ACCV 2009).

• Zhang, W., Wu, J., & Wang, G. (2009). Vehicle headlights detection using Markov random fields. In Asian Conference on Computer Vision (ACCV 2009).

• Zhang, Z., Wang, G., & Wu, J. (2009). Face recognition based on wavelet-curvelet-fractal technique. In Lecture Notes in Computer Science (ICIAR 2009) (Vol. 5627).

2008

• Wang, G., & Wu, J. (2008). Stratification approach for 3D Euclidean reconstruction of nonrigid objects from uncalibrated image sequences. IEEE Trans. on Systems, Man, and Cybernetics: Part B (T-SMCB), 38(1), 90-101. , (impact factor: 6.220) (12 pages)

• Wang, G., Tsui, H., & Wu, J. (2008). Rotation constrained power factorization for structure from motion of nonrigid objects. Pattern Recognition Letters, 29(1), 72-80. , (impact factor: 1.995) (9 pages)

• Wang, G., Wu, J., & Ji, Z. (2008). Single view based pose estimation from circle or parallel lines. Pattern Recognition Letters, 29(7), 977-985. , (impact factor: 1.995) (9 pages)

• Wang, G., Wu, J., & Zhang, W. (2008). Kruppa equation based camera calibration from homography induced by remote plane. Pattern Recognition Letters, 29(16), 2137-2144. , (impact factor: 1.995) (8 pages)

• Wang, G., & Wu, J. (2008). Quasi-perspective projection with applications to 3D factorization from uncalibrated image sequences. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008).

• Wang, G., & Wu, J. (2008). Camera self-calibration and three dimensional reconstruction under quasi-perspective projection. In Canadian Conference on Computer and Robot Vision (CRV 2008) (pp. 129-136).

• Wang, G., & Wu, J. (2008). Camera self-calibration under the constraint of distant plane. In Lecture Notes in Computer Science (RobVis 2008) (Vol. 4391).

• Wang, G., & Wu, J. (2008). Euclidean structure and motion from uncalibrated image sequences under perspective projection. In International Conference on Signal Processing (ICSP 2008).

• Wang, G., & Wu, J. (2008). Structure and motion factorization under quasi-perspective projection with missing data in tracking matrix. In International Conference on Pattern Recognition (ICPR 2008).

• Zhang, W., Wu, J., & Wang, G. (2008). Adaptive semantic Bayesian framework for image attention. In International Conference on Pattern Recognition (ICPR 2008).

• Wang, G., Tsui, H., & Hu, Z. (2007). Structure and motion of nonrigid object under perspective projection. Pattern Recognition Letters, 28(4), 507-515. , (impact factor: 1.995) (9 pages)

• Wang, G., & Wu, J. (2007). Deformation weight constraint and 3D reconstruction of nonrigid objects. In Lecture Notes in Computer Science (ICIAR 2007) (Vol. 4633, pp. 258-294).

• Wang, G., & Wu, J. (2007). Pose estimation from circle or parallel lines in a single image. In Lecture Notes in Computer Science (ACCV 2007) (Vol. 4844).

2006

• Wu, Y., Wang, G., et al. (2006). Euclidean reconstruction of a circular truncated cone only from its uncalibrated contours. Image and Vision Computing, 24(8), 810-818. , (impact factor: 2.671) (9 pages)

• Wang, G., & Wu, J. (2006). Modelling nonrigid objects from video sequences based on power factorization. In ICAT Workshops 2006 (pp. 98-103).

• Wang, G. (2006). Three dimensional reconstruction of structured scenes based on vanishing points. In Lecture Notes in Computer Science (PCM 2006) (Vol. 4261, pp. 927-934).

• Wang, G., Hu, Z., et al. (2005). Single view metrology from scene constraints. Image and Vision Computing, 23(9), 831-840. , (impact factor: 2.671) (10 pages)

• Wang, G., Tsui, H., et al. (2005). Camera calibration and 3D reconstruction from a single view based on scene constraints. Image and Vision Computing, 23(3), 311-323. , (impact factor: 2.671) (13 pages)

• Wang, G., et al. (2005). Modelling nonrigid object from video sequence under perspective projection. In Lecture Notes in Computer Science (ACII 2005) (Vol. 3784, pp. 64-71).

2004

• Wang, G., Hu, Z., et al. (2004). Implementation and experimental study on fast object modelling based on multiple structured stripes. Optics and Lasers in Engineering, 42(6), 627-638. , (impact factor: 2.769) (12 pages)

• Wang, G., Hu, Z., et al. (2004). Single view based measurement on space planes. Journal of Computer Science and Technology, 19(3), 374-382. , (impact factor: 0.956) (9 pages)

• Wang, G., Tsui, H., et al. (2004). Reconstruction of structured scenes from two uncalibrated images. Pattern Recognition Letters, 26(2), 207-220. , (impact factor: 1.995) (14 pages)

• Wang, G., et al. (2004). Camera calibration from a single view of structured scenes. In Asian Conference on Computer Vision (ACCV 2004).

• Hu, Z., Wu, F., & Wang, G. (2003). The impossibility of affine reconstruction from perspective image pairs obtained by a translating camera with varying parameters. Pattern Recognition Letters, 24(16), 2909-2911. , (impact factor: 1.995)

• Li, Q., & Wang, G. (2003). Symmetric PH and EP distributions and their applications to the probability Hough transform. Computers and Mathematics with Applications, 47(6-7), 823-844. , (impact factor: 1.531) (22 pages)

• Wang, G., et al. (2003). Projector-camera based system for fast object modeling. In IEEE International Workshop on Projector-Camera Systems (In ICCV 2003).

2002

• Hong, W., Tian, Y., Dong, Z., & Wang, G. (2002). Research about obstacle group for autonomous mobile robots. Journal of Jilin University (Information Science Edition), 20(1).

• Hu, Z., & Wang, G. (2002). Affine reconstruction from planes and lines. Chinese Journal of Computers, 26(6), 10 pages.

• Wang, G., et al. (2002). An obstacle-cluster based data fusion method for mobile robots. Journal of Basic Science and Engineering, 5(2), 9 pages.

• Wang, G., et al. (2002). Control and experiment study of super articulated tandem pendulum. Control Theory and Application, 17(6).

• Wu, F., & Wang, G. (2002). A linear approach for determining intrinsic parameters and pose cameras from rectangles. Chinese Journal of Software, 14(3). (9 pages)

• Li, H., Wang, G., et al. (2002). A new self-calibration technique via epipoles. In Asian Conference on Computer Vision (ACCV 2002).

• Wang, G., et al. (2002). A novel approach for single view based plane metrology. In International Conference on Pattern Recognition (ICPR 2002).

• Wang, G., et al. (2002). Novel approach to circular points based camera calibration. In Proceedings of SPIE (Vol. 4875).

• Wu, F., Wang, G., & Hu, Z. (2002). Affine reconstruction from a plane and two parallel lines. In Proceedings of SPIE (ICIG 2002) (Vol. 4875).

• Wang, G., et al. (2001). Experimental study of magnetic suspension system. In CASIA Annual Conference on Automation and Information Technology.

• Wang, G., et al. (2001). Stabilization and control of super articulated ball and beam system. In World Conference on Intelligent Control and Automation (WCICA 2001).

• Dong, Z., & Wang, G. (2000). Laser-based global location for autonomous mobile robots. Journal of Robotics, 22(3).

• Wang, G., & Tian, Y. (2000). Stabilization and control of super articulated tandem pendulums. Journal of Robotics, 21(7).

   

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