Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Nanyang Associate Professor, School of Computer Science and EngineeringNTU Co-Associate Lab Director, SenseTime-NTU Joint Research Centre Mach. Facial landmark detection has long been impeded by the problems of occlusion and pose variation. Image Super-Resolution Using Deep Convolutional Networks. He received his PhD (2010) in Computer Science from the Queen Mary University of London. Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore.He is also an Adjunct Associate Professor at the Chinese University of Hong Kong. Non-Local Recurrent Network for Image Restoration. 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. Person Re-Identification: What Features are Important? Dr Loy's research interests include computer vision and deep learning. Deep Network Interpolation for Continuous Imagery Effect Transition. He, C. Li, C. C. Loy, Z. Liu, TransGaGa: Geometry-Aware Unsupervised Image-to-Image Translation, Disentangling Content and Style via Unsupervised Geometry Distillation, Instance-level Facial Attributes Transfer with Geometry-aware Flow, ReenactGAN: Learning to Reenact Faces via Boundary Transfer, W. Wu, Y. Zhang, C. Li, C. Qian, C. C. Loy, Dense Intrinsic Appearance Flow for Human Pose Transfer, W. Shi, T.-W. Hui, Z. Liu, D. Lin, C. C. Loy, Be Your Own Prada: Fashion Synthesis with Structural Coherence, S. Zhu, S. Fidler, R. Urtasun, D. Lin, C. C. Loy, TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting, Z. Yang, W. Zhu, W. Wu, C. Qian, Q. Zhou, B. Zhou, C. C. Loy, High-Quality Video Generation from Static Structural Annotations, L. Sheng, J. Pan, J. Guo, J. Shao, C. C. Loy, Unsupervised Bi-directional Flow-based Video Generation from one Snapshot, L. Sheng, J. Pan, J. Guo, J. Shao, X. Wang, C. C. Loy, Chasing the Tail in Monocular 3D Human Reconstruction with Prototype Memory, Delving Deep into Hybrid Annotations for 3D Human Recovery in the Wild, Y. Rong, Z. Liu, C. Li, K. Cao, C. C. Loy, Multi-Modality Cut and Paste for 3D Object Detection, Side-Aware Boundary Localization for More Precise Object Detection, J. Wang, W. Zhang, Y. Cao, K. Chen, J. Pang, T. Gong, J. Shi, C. C. Loy, D. Lin, RGB-D Salient Object Detection with Cross-Modality Modulation and Selection, C. Li, R. Cong, Y. Piao, Q. Xu, C. C. Loy, K. Chen, Y. Cao, C. C. Loy, D. Lin, C. Feichtenhofer, Prime Sample Attention in Object Detection, CARAFE: Content-Aware ReAssembly of FEatures, J. Wang, K. Chen, R. Xu, Z. Liu, C. C. Loy, D. Lin, MMDetection: Open MMLab Detection Toolbox and Benchmark, K. Chen, J. Wang, J. Pang, Y. Cao, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Xu, Z. Zhang, D. Cheng, C. Zhu, T. Cheng, Q. Zhao, B. Li, X. Lu, R. Zhu, Y. Wu, J. Dai, J. Wang, J. Shi, W. Ouyang, C. C. Loy, D. Lin, Hybrid Task Cascade for Instance Segmentation, K. Chen, J. Pang, J. Wang, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Shi, W. Ouyang, C. C. Loy, D. Lin, J. Wang, K. Chen, S. Yang, C. C. Loy, D. Lin, Optimizing Video Object Detection via a Scale-Time Lattice, K. Chen, J. Wang, S. Yang, X. Zhang, Y. Xiong, C. C. Loy, D. Lin, Fusing Object Context to Detect Functional Area for Cognitive Robots, H. Cheng, J. Cai, Q. Liu, Z. Zhang, K. Yang, C. C. Loy, L. Lin, Discover and Learn New Objects from Documentaries, DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks, W. Ouyang, X. Zeng, X. Wang, S. Qiu, P. Luo, Y. Tian, H. Li, S. Yang, Z. Wang, H. Li, K. Wang, J. Yan, C. C. Loy, X. Tang, DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection, W. Ouyang, X. Wang, X. Zeng, S. Qiu, P. Luo, Y. Tian, H. Li, S. Yang, Z. Wang, C. C. Loy, X. Tang, DeepID-Net: Multi-stage and Deformable Deep Convolutional Neural Network for Generic Object Detection, W. Ouyang, P. Luo, X. Zeng, S. Qiu, Y. Tian, H. Li, S. Yang, Z. Wang, Y. Xiong, C. Qian, Z. Zhu, R. Wang, C. C. Loy, X. Wang, X. Tang, Seesaw Loss for Long-Tailed Instance Segmentation, J. Wang, W. Zhang, Y. Zang, Y. Cao, J. Pang, T. Gong, K. Chen, Z. Liu, C. C. Loy, D. Lin, Video Object Segmentation with Joint Re-identification and Attention-Aware Mask Propagation, PSANet: Point-wise Spatial Attention Network for Scene Parsing, H. Zhao, Y. Zhang, S. Liu, J. Shi, C. C. Loy, D. Lin, J. Jia, Mix-and-Match Tuning for Self-supervised Semantic Segmentation, X. Zhan, Z. Liu, P. Luo, X. Tang, C. C. Loy, Video Object Segmentation with Re-identification, X. Li, Y. Qi, Z. Wang. Chen Change Loy Nanyang Technological University Singapore: G2R World Ranking 1059th. 96. results. Prior to joining NTU, he served as a Research Assistant Professor at the MMLab of the Chinese University of Hong Kong, from 2013 to 2018. (2019). 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, Everybody’s Talkin’: 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. ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. Loy Chen Change is an Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Instead of treating the detection task as a single and independent problem, we investigate the possibility of improving detection robustness through multi-task learning. Accelerating the Super-Resolution Convolutional Neural Network. 2013, he was a postdoctoral researcher at Vision Semantics Ltd. X. Wang, K. Yu, S. Wu, J. Gu, Y. Liu, C. Dong, Y. Qiao, C. C. Loy. Deep Flow-Guided Video Inpainting. He is also an Adjunct Associate Professor at the Chinese University of Hong Kong. - xinntao/EDVR Semantic Scholar profile for Chen Change Loy, with 3344 highly influential citations and 203 scientific research papers. Person Re-Identification (Advances in Computer Vision and Pattern Recognition) [Gong, Shaogang, Cristani, Marco, Yan, Shuicheng, Loy, Chen Change] on Amazon.com. He received his PhD (2010) in Computer Science from the Queen Mary University of London. Chen Change Loy Machine Learning Researcher. Xintao Wang. You may be trying to access this site from a secured browser on the server. Person Re-Identification (Advances in Computer Vision and Pattern Recognition) Authors: Chao Dong, Chen Change Loy, Xiaoou Tang. New LiteFlowNet3: Resolving Correspondence Ambiguity for More Accurate Optical Flow Estimation T.-W. Hui, C. C. Loy European Conference on Computer Vision, 2020 (ECCV) PDF Technical Report Supplementary Material Project Page | Codes; New [LiteFlowNet2] A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization T.-W. Hui, X. Tang, C. C. Loy ), V. Murino, S. Gong, C. C. Loy, L. Bazzani (Eds. G2R Singapore Ranking 14th. "Scene-Independent Group Profiling in Crowd." Loy Chen Change is an Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. 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. H-Index & Metrics. Xintao Wang, Kelvin C.K. Google H-index: 68: Number of Google Citations: 25,187: Number of Articles on DBLP: 206: External Links. Chen Huang, Yining Li, Chen Change Loy, Xiaoou Tang: Deep Imbalanced Learning for Face Recognition and Attribute Prediction. Our method directly learns an end-to-end mapping between the low/high-resolution images. Email: ccloy@ntu.edu.sg Assoc Prof Chen Change Loy, Copyright • Disclaimer • NTU Privacy Statement Reg. 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. Chan, Ke Yu, Chao Dong, Chen Change Loy Computer Vision and Pattern Recognition Workshops (CVPRW), 2019 Champions, NTIRE 2019 Challenges on Video Restoration and Enhancement [ Paper (arXiv) ] [ Project Page] [ Codes ] In Proceedings of European Conference on Computer Vision (ECCV), 2018 [Project Page] Learning to Cluster Faces via Confidence and Connectivity Estimation. Research Areas. He was a postdoctoral researcher at Queen Mary University of London and Vision Semantics Limited, from 2010 to 2013. We further show that traditional sparse-coding-based SR … X. Wang, K. Yu, C. Dong, X. Tang, C. C. Loy. ), S. Gong, M. Cristani, C. C. Loy, and T. Hospedales, Evaluating Feature Importance for Re-Identification, POP: Person Re-Identification Post-Rank Optimisation, Person Re-Identification by Manifold Ranking. Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. 42 ( 11 ) : 2781-2794 ( 2020 ) Fan, C. C. Loy, T. S. Huang. Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. (2015). 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. Abstract. Person Re-Identification - Ebook written by Shaogang Gong, Marco Cristani, Shuicheng Yan, 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. No. Learning to Group Faces via Imitation Learning, Joint Face Representation Adaptation and Clustering in Videos, A Survey on Heterogeneous Face Recognition: Sketch, Infra-red, 3D and Low-Resolution, S. Ouyang, T. Hospedales, Y. D. Liu, B. Wen, Y. He got his Ph.D. degree from Multimedia Laboratory, The Chinese University of Hong Kong, supervised by Prof. Xiaoou Tang and Prof. Chen Change Loy.He also works closely with Prof. Chao Dong.Previously, He received the B. Eng degree from Zhejiang University in 2016. IEEE Trans. Student exchange and short-term mobility programmes, TRACS (Talent Recruitment and Career Support Office). Verified email at ntu.edu.sg - … Download PDF Abstract: As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) has demonstrated superior performance to the previous hand-crafted models either in speed and restoration quality. We propose a deep learning method for single image super-resolution (SR). ), 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. Please enable scripts and reload this page. From Dec. 2010 – Mar. Chen Change Loy (S'06-M'10-SM'17) received the PhD degree in computer science from the Queen Mary University of London, in 2010. 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. Hybrid Task Cascade for Instance Segmentation Cascade is a classic yet powerful architecture that has … Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. (2019). He received his PhD (2010) in Computer Science from the Queen Mary University of London.Prior to joining NTU, he served as a Research Assistant Professor at the … ∙ 6 ∙ share read it. Jing Shao, Chen Change Loy, and Xiaogang Wang. Optical Flow Estimation. Nanyang Technological University. Chao Dong, Chen Change Loy, Xiaoou Tang. Read this book using Google Play Books app on your PC, android, iOS devices. Chen Change Loy is a Research Assistant Professor in the Chinese University of Hong Kong. (2018). 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. 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? 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. Jing Shao, Chen Change Loy, and Xiaogang Wang. Song, T. Xiang, T. M. Hospedales, C. C. Loy, Reading Scene Text in Deep Convolutional Sequences, P. He, W. Huang, Y. Qiao, C. C. Loy, X. Tang, Zoom-Net: Mining Deep Feature Interactions for Visual Relationship Recognition, G. Yin, L. Sheng, B. Liu, N. Yu, X. Wang, J. Shao, C. C. Loy, Learning to Disambiguate by Asking Discriminative Questions, Development of Fine-grained Pill Identification Algorithm using Deep Convolutional Network, Y. F. Wong, H. T. Ng, K. Y. Leung, K. Y. Chan, S. Y. Chan, C. C. Loy, Robust and Fast Decoding of High-Capacity Color QR Codes for Mobile Applications, Z. Yang, H. Xu, J. Deng, C. C. Loy, W. C. Lau, Towards Robust Color Recovery for High-Capacity Color QR Codes, Z. Yang, Z. Cheng, C. C. Loy, W. C. Lau, C. M. Li, G. Li, Authenticating the Identity of Computer Users with Typing Biometrics and the Fuzzy Min-Max Neural Network, A. Quteishat, C. P. Lim, C. C. Loy, and W. K. Lai, Keystroke Patterns Classification using the ARTMAP-FD Neural Network, Pressure-based Typing Biometrics User Authentication Using The Fuzzy ARTMAP Neural Network, The Development of a Pressure-based Typing Biometrics User Authentication System, Classification of Computer System Users through Keystroke Dynamics, C. C. Loy, I. Hanum, C. P. Lim, W. K. Lai, Robust Modular ARTMAP for Multi-Class Shape Recognition, C. P. Tan, C. C. Loy, W. K. Lai, and C. P. Lim, Modular ARTMAP for Multi-Class Pattern Recognition, Use of Circle-Segments as a Data Visualization Technique for Feature Selection in Pattern Classification, S. L. Wang, C. C. Loy, C. P. Lim, W. K. Lai, and K. S. Tan, Needle in a Data Haystack: Finding Similarities in High-Dimensional Data, Investigation into the Use of N-grams for Ovarian Cancer Identification, Z. 02/19/2019 ∙ by Chen Change Loy, et al. in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. 109. papers. Pattern Anal. *FREE* shipping on qualifying offers. Citation Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. Chen Change Loy is a Nanyang Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. 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. Intell. "Learning Scene-Independent Group … (2018). 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. He, X. Tang, C. C. Loy, L. Bazzani ( Eds L. Bazzani ( Eds Li, Zhou! Nanyang Associate Professor with the School of Computer Science from the Queen Mary University of and... Learns an end-to-end mapping between the low/high-resolution images robustness through multi-task learning et al Assistant Professor in the Chinese of... Merged into BasicSR and this repo is a Research Assistant Professor in the Chinese University of Hong Authors. 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