chen change loy

Person Re-Identification: What Features are Important? Intell. Instead of treating the detection task as a single and independent problem, we investigate the possibility of improving detection robustness through multi-task learning. Student exchange and short-term mobility programmes, TRACS (Talent Recruitment and Career Support Office). We propose a deep learning method for single image super-resolution (SR). K. Chen, Z. Liu, J. Shi, P. Luo, X. Tang, C. C. Loy, Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade, X. Li, Z. Liu, P. Luo, C. C. Loy, X. Tang, Deep Learning Markov Random Field for Semantic Segmentation, Z. Liu, X. Li, P. Luo, C. C. Loy, X. Tang, Semantic Image Segmentation via Deep Parsing Network, EcoNAS: Finding Proxies for Economical Neural Architecture Search, D. Zhou, X. Zhou, W. Zhang, C. C. Loy, S. Yi, X. Zhang, W. Ouyang, PolyNet: A Pursuit of Structural Diversity in Very Deep Networks, Local Similarity-Aware Deep Feature Embedding, Unsupervised Learning of Discriminative Attributes and Visual Representations, Learning Deep Representation for Imbalanced Classification, Deep Representation Learning with Target Coding, S. Yang, P. Luo, C. C. Loy, K. W. Shum, X. Tang, MessyTable: Instance Association in Multiple Camera Views, Z. Cai, J. Zhang, D. Ren, C. Yu, H. Zhao, S. Yi, C. K. Yeo, C. C. Loy, Robust Multi-Modality Multi-Object Tracking, W. Zhang, H. Zhou, S. Sun, Z. Wang, J. Shi, C. C. Loy, Delving into Inter-Image Invariance for Unsupervised Visual Representations, J. Xie, X. Zhan, Z. Liu, Y. S. Ong, C. C. Loy, Online Deep Clustering for Unsupervised Representation Learning, X. Zhan, J. Xie, Z. Liu, Y. S. Ong, C. C. Loy, Self-Supervised Learning via Conditional Motion Propagation, X. Zhan, X. Pan, Z. Liu, D. Lin, C. C. Loy, Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup, Knowledge Distillation Meets Self-Supervision, Inter-Region Affinity Distillation for Road Marking Segmentation, Y. Hou, Z. Ma, C. Liu, T.-W. Hui, C. C. Loy, Learning Lightweight Lane Detection CNNs by Self Attention Distillation, Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks, Feature Matters: A Stage-by-Stage Approach for Knowledge Transfer, M. Gao, Y. Shen, Q. Li, C. C. Loy, X. Tang, Learning a Unified Classifier Incrementally via Rebalancing, S. Hou, X. Pan, C. C. Loy, Z. Wang, D. Lin, Lifelong Learning via Progressive Distillation and Retrospection, Improving On-policy Learning with Statistical Reward Accumulation, Y. Deng, K. Yu, D. Lin, X. Tang, C. C. Loy, Deep Imbalanced Learning for Face Recognition and Attribute Prediction, Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition, X. Zhan, Z. Liu, J. Yan, D. Lin, C. C. Loy, The Devil of Face Recognition is in the Noise, F. Wang, L. Chen, C. Li, S. Huang, Y. Chen, C. Qian, C. C. Loy, Pose-Robust Face Recognition via Deep Residual Equivariant Mapping, K. Cao, Y. Rong, C. Li, X. Tang, C. C. Loy, WIDER Face and Pedestrian Challenge 2018: Methods and Results. C. C. Loy, D. Lin, W. Ouyang, Y. Xiong, S. Yang, Q. Huang, D. Zhou, W. Xia, Q. Li, P. Luo, J. Yan, et al. The mapping is represented as a deep convolutional neural network (CNN) that takes the low-resolution image as the input and outputs the high-resolution one. Non-Local Recurrent Network for Image Restoration. Please enable scripts and reload this page. 2018/10-2020/01, I was a postdoctoral fellow and worked with Prof. Sam Kwong (IEEE Fellow), Department of Computer Science, City University of Hong Kong (CityU), Kowloon, Hong Kong. Person Re-Identification (Advances in Computer Vision and Pattern Recognition) In Proceedings of European Conference on Computer Vision (ECCV), 2018 [Project Page] Learning to Cluster Faces via Confidence and Connectivity Estimation. We propose a deep learning method for single image super-resolution (SR). Person Re-Identification - Ebook written by Shaogang Gong, Marco Cristani, Shuicheng Yan, Chen Change Loy. C. Dong, C. C. Loy, K. He, X. Tang. He is also an Adjunct Associate Professor at the Chinese University of Hong Kong, and a visiting scholar of Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China. Authors: Chao Dong, Chen Change Loy, Xiaoou Tang. Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. X. Wang, K. Yu, S. Wu, J. Gu, Y. Liu, C. Dong, Y. Qiao, C. C. Loy. BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond, Kelvin C. K. Chan, X. Wang, K. Yu, C. Dong, C. C. Loy, GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution, Kelvin C. K. Chan, X. Wang, X. Xu, J. Gu, C. C. Loy, Understanding Deformable Alignment in Video Super-Resolution, K. C. K. Chan, X. Wang, K. Yu, C. Dong, C. C. Loy, Cross-Scale Internal Graph Neural Network for Image Super-Resolution, Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation, X. Pan, X. Zhan, B. Dai, D. Lin, C. C. Loy, P. Luo, Deep Network Interpolation for Continuous Imagery Effect Transition, X. Wang, K. Yu, C. Dong, X. Tang, C. C. Loy, Non-Local Recurrent Network for Image Restoration, D. Liu, B. Wen, Y. ), V. Murino, S. Gong, C. C. Loy, L. Bazzani (Eds. (2019). Hybrid Task Cascade for Instance Segmentation Cascade is a classic yet powerful architecture that has … Xintao is a researcher at Tencent ARC Lab, (Applied Research Center, Shenzhen). Chen Change Loy. Learning a Deep Convolutional Network for Image Super-Resolution, in Proceedings of European Conference on Computer Vision (ECCV), 2014 PDF Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. Person Re-Identification (Advances in Computer Vision and Pattern Recognition) [Gong, Shaogang, Cristani, Marco, Yan, Shuicheng, Loy, Chen Change] on Amazon.com. D. Liu, B. Wen, Y. 96. results. Our method directly learns an end-to-end mapping between the low/high-resolution images. 109. papers. (2018). Accelerating the Super-Resolution Convolutional Neural Network. Face Detection through Scale-Friendly Deep Convolutional Networks, Faceness-Net: Face Detection through Deep Facial Part Responses, From Facial Part Responses to Face Detection: A Deep Learning Approach, Unconstrained Face Alignment via Cascaded Compositional Learning, Learning Deep Representation for Face Alignment with Auxiliary Attributes, Face Alignment by Coarse-to-Fine Shape Searching, Towards Arbitrary-View Face Alignment by Recommendation Trees, An Empirical Study of Recent Face Alignment Methods, Facial Landmark Detection by Deep Multi-task Learning, Transferring Landmark Annotations for Cross-Dataset Face Alignment, From Facial Expression Recognition to Interpersonal Relation Prediction, Quantifying Facial Age by Posterior of Age Comparisons, Discriminative Sparse Neighbor Approximation for Imbalanced Learning, Deep Learning Face Attributes for Face Detection and Alignment, Learning Social Relation Traits from Face Images, Cumulative Attribute Space for Age and Crowd Density Estimation, K. Chen, S. Gong, T. Xiang, and C. C. Loy, Learning to Cluster Faces via Confidence and Connectivity Estimation, L. Yang, D. Chen, X. Zhan, R. Zhao, C. C. Loy, D. Lin, Learning to Cluster Faces on an Affinity Graph, L. Yang, X. Zhan, D. Chen, J. Yan, C. C. Loy, D. Lin, Merge or Not? 200604393R, © 2012 Nanyang Technological University Last modified on 28-Mar-2019. Chen Change Loy Nanyang Technological University Singapore: G2R World Ranking 1059th. We further show that traditional sparse-coding-based SR … You may be trying to access this site from a secured browser on the server. Download for offline reading, highlight, bookmark or take notes while you read Person Re-Identification. … Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. (2019). Assoc Prof Chen Change Loy Email: ccloy@ntu.edu.sg Assoc Prof Chen Change Loy, Copyright • Disclaimer • NTU Privacy Statement Reg. Lei Yang, Dapeng Chen, Xiaohang Zhan, Rui Zhao, Chen Change Loy… Image Super-Resolution Using Deep Convolutional Networks. ∙ 6 ∙ share read it. R. Xu, X. Li, B. Zhou, C. C. Loy. "Learning Scene-Independent Group … Jing Shao, Chen Change Loy, and Xiaogang Wang. Loy Chen Change is an Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Facial landmark detection has long been impeded by the problems of occlusion and pose variation. Z. Sharifah, C. C. Loy, S. Y. Tai, and W. K. Lai, Dimensionality Reduction of Protein Mass Spectrometry Data Using Random Projection, C. C. Loy, X. Liu, T.-K. Kim, F. De la Torre, R. Chellappa (Eds. He received his PhD (2010) in Computer Science from the Queen Mary University of London. Research Areas. ), S. Gong, M. Cristani, C. C. Loy and T. Hospedales, A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization, CARAFE++: Unified Content-Aware ReAssembly of FEatures, Image and Video Understanding in Big Data. Xiaohang Zhan, Ziwei Liu, Junjie Yan, Dahua Lin, Chen Change Loy. ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. Mach. Fan, C. C. Loy, T. S. Huang. 2020/01-now, I join in the MMLab@NTU as a research fellow and work with Dr. Chen Change Loy, School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore. No. Chao Dong, Chen Change Loy, Xiaoou Tang. Read this book using Google Play Books app on your PC, android, iOS devices. IEEE Trans. From Dec. 2010 – Mar. Song, X. Li, C. C. Loy, X. Wang, Incremental Activity Modelling in Multiple Disjoint Cameras, Comparing Visual Feature Coding for Learning Disjoint Camera Dependencies, Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding, Modelling Activity Global Temporal Dependencies using Time Delayed Probabilistic Graphical Model, Multi-Camera Activity Correlation Analysis, Pedestrian Color Naming via Convolutional Neural Network, Human Attribute Recognition by Deep Hierarchical Contexts, Pedestrian Attribute Recognition At Far Distance, On-the-fly Feature Importance Mining for Person Re-Identification, S. Gong, M. Cristani, S. Yan, C. C. Loy (Eds. Chen Change Loy is a Research Assistant Professor in the Chinese University of Hong Kong. Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. Department of Information Engineering, The Chinese University of Hong Kong Citation Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. 2013, he was a postdoctoral researcher at Vision Semantics Ltd. Loy Chen Change is an Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Xintao Wang, Kelvin C.K. Unsupervised 3D shape reconstruction from 2D Image GANs, X. Pan, B. Dai, Z. Liu, C. C. Loy, P. Luo, Focal Frequency Loss for Generative Models, Positional Encoding as Spatial Inductive Bias in GANs, R. Xu, X. Wang, K. Chen, B. Zhou, C. C. Loy, TSIT: A Simple and Versatile Framework for Image-to-Image Translation, L. Jiang, C. Zhang, M. Huang, C. Liu, J. Shi, C. C. Loy, MEAD: A Large-scale Audio-visual Dataset for Emotional Talking Face Generation, K. Wang, Q. Wu, L. Song, Z. Yang, W. Wu, C. Qian, R. He, Y. Qiao, C. C. Loy, X. Zhan, X. Pan, B. Dai, Z. Liu, D. Lin, C. C. Loy, DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection, L. Jiang, W. Wu, R. Li, C. Qian, C. C. Loy, Everybodyâs Talkinâ: Let Me Talk as You Want, L. Song, W. Wu, C. Qian, R. He, C. C. Loy, Y. Xiangli, Y. Deng, B. Dai, C. C. Loy, D. Lin, Y. Zhang, S. Zhang, Y. He received his PhD ( 2010 ) in Computer Science from the Queen Mary of..., Xiaoou Tang 's Research interests include Computer Vision and deep learning method for single image super-resolution SR. Secured browser on the server Loy 's Research interests include Computer Vision and deep learning by Chen Change Loy Technological... Xiaogang Wang from 2010 to 2013 2012 Nanyang Technological University, Singapore, C. C. Loy, T. S..... A postdoctoral researcher at Tencent ARC Lab, ( Applied Research Center, Shenzhen ) reading! Detection has long been impeded by the problems of occlusion and pose variation::... 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