World's Best Scientists 2026 revealed!
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Computer Science
Singapore
2026

D-Index & Metrics

Computer Science

D-Index
118
Citations
82452
World Ranking
156
National Ranking
6

Research.com Recognitions

  • 2026 - Research.com Computer Science in Singapore Leader Award
  • 2025 - Research.com Computer Science in Singapore Leader Award
  • 2023 - Research.com Computer Science in Singapore Leader Award
  • 2022 - Research.com Computer Science in Singapore Leader Award

Overview

Chen Change Loy is affiliated with Nanyang Technological University in Singapore and specializes in computer science with a strong focus on computer vision and pattern recognition. Their research portfolio encompasses several subfields including artificial intelligence, computational mechanics, media technology, and computer graphics and computer-aided design.

Their work spans multiple main topics of research such as generative adversarial networks and image synthesis, advanced image processing techniques, advanced vision and imaging, advanced neural network applications, domain adaptation and few-shot learning, multimodal machine learning applications, and human pose and action recognition.

Chen Change Loy has frequently published in the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • International Journal of Computer Vision
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Proceedings of the AAAI Conference on Artificial Intelligence

Notable recent papers authored by or involving Chen Change Loy include:

  • Learning to Prompt for Vision-Language Models, 2022, International Journal of Computer Vision
  • Conditional Prompt Learning for Vision-Language Models, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Domain Generalization: A Survey, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • MMDetection: Open MMLab Detection Toolbox and Benchmark, 2024, arXiv (Cornell University)
  • Low-Light Image and Video Enhancement Using Deep Learning: A Survey, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence

The scientist's frequent coauthors include:

  • Ziwei Liu
  • Shangchen Zhou
  • Chongyi Li
  • Wayne Wu
  • Ruicheng Feng

Chen Change Loy has contributed extensively to the computer vision and pattern recognition communities, as reflected in their prolific publication record and collaborations. Their interdisciplinary interests bridge core topics in artificial intelligence with applications in image synthesis, neural network design, and multimodal learning techniques.

Best Publications

  • Image Super-Resolution Using Deep Convolutional Networks

    Chao Dong;Chen Change Loy;Kaiming He;Xiaoou Tang

  • Learning a Deep Convolutional Network for Image Super-Resolution

    Chao Dong;Chen Change Loy;Kaiming He;Xiaoou Tang

  • ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

    Xintao Wang;Ke Yu;Shixiang Wu;Jinjin Gu

  • Accelerating the Super-Resolution Convolutional Neural Network

    Chao Dong;Chen Change Loy;Xiaoou Tang

  • Learning to Prompt for Vision-Language Models

    Unknown

  • Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

    Chunle Guo;Chongyi Li;Jichang Guo;Chen Change Loy

  • WIDER FACE: A Face Detection Benchmark

    Shuo Yang;Ping Luo;Chen Change Loy;Xiaoou Tang

  • Conditional Prompt Learning for Vision-Language Models

    Unknown

  • Facial Landmark Detection by Deep Multi-task Learning

    Zhanpeng Zhang;Ping Luo;Chen Change Loy;Xiaoou Tang

  • NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

    Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang

  • Hybrid Task Cascade for Instance Segmentation

    Kai Chen;Wanli Ouyang;Chen Change Loy;Dahua Lin

  • Domain Generalization: A Survey

    Unknown

  • ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

    Xintao Wang;Ke Yu;Shixiang Wu;Jinjin Gu

  • PSANet: Point-wise Spatial Attention Network for Scene Parsing

    Hengshuang Zhao;Yi Zhang;Shu Liu;Jianping Shi

  • EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

    Xintao Wang;Kelvin C.K. Chan;Ke Yu;Chao Dong

  • Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform

    Xintao Wang;Ke Yu;Chao Dong;Chen Change Loy

  • Learning Deep Representation for Imbalanced Classification

    Chen Huang;Yining Li;Chen Change Loy;Xiaoou Tang

  • Learning a Unified Classifier Incrementally via Rebalancing

    Saihui Hou;Xinyu Pan;Chen Change Loy;Zilei Wang

  • A large-scale car dataset for fine-grained categorization and verification

    Linjie Yang;Ping Luo;Chen Change Loy;Xiaoou Tang

  • Compression Artifacts Reduction by a Deep Convolutional Network

    Chao Dong;Yubin Deng;Chen Change Loy;Xiaoou Tang

  • MMDetection: Open MMLab Detection Toolbox and Benchmark.

    Kai Chen;Jiaqi Wang;Jiangmiao Pang;Yuhang Cao

  • Semantic Image Segmentation via Deep Parsing Network

    Ziwei Liu;Xiaoxiao Li;Ping Luo;Chen-Change Loy

  • Feature mining for localised crowd counting

    Ke Chen;Chen Change Loy;Shaogang Gong;Tony Xiang

Frequent Co-Authors

Xiaoou Tang
Xiaoou Tang Chinese University of Hong Kong
Ping Luo
Ping Luo University of Hong Kong
Dahua Lin
Dahua Lin Chinese University of Hong Kong
Shaogang Gong
Shaogang Gong Queen Mary University of London
Ziwei Liu
Ziwei Liu Nanyang Technological University
Chao Dong
Chao Dong Shenzhen Institutes of Advanced Technology
Xiaogang Wang
Xiaogang Wang Chinese University of Hong Kong
Wanli Ouyang
Wanli Ouyang Shanghai AI Lab
Jianping Shi
Jianping Shi SenseTime
Xiatian Zhu
Xiatian Zhu University of Surrey

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