World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
19924
World Ranking
4443
National Ranking
598

Overview

Chang Huang is affiliated with Horizon Robotics Inc. in China and has contributed significantly to both Environmental Science and Computer Science. Their research spans a range of interdisciplinary topics, with a focus on the application of advanced computational methods within environmental and vision-related domains.

Their work addresses main fields of study including:

  • Environmental Science
  • Computer Science

Within these broad areas, Chang Huang's subfields of research include:

  • Computer Vision and Pattern Recognition
  • Global and Planetary Change
  • Atmospheric Science
  • Ecology
  • Water Science and Technology

The main research topics covered in their publications are:

  • Flood Risk Assessment and Management
  • Hydrology and Watershed Management Studies
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Land Use and Ecosystem Services
  • Video Surveillance and Tracking Methods
  • Domain Adaptation and Few-Shot Learning

Chang Huang has published papers in a variety of venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Remote Sensing
  • Water
  • SSRN Electronic Journal
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Frequent co-authors in their collaborative work include:

  • Xinggang Wang (21 publications)
  • Wenyu Liu (19 publications)
  • Shaoyu Chen (15 publications)
  • Tianheng Cheng (12 publications)
  • Qian Zhang (11 publications)

Recent representative papers by Chang Huang comprise:

  • Do major customers encourage innovative sustainable development? Empirical evidence from corporate green innovation in China, 2022, Business Strategy and the Environment
  • Unsupervised domain adaptive re-identification: Theory and practice, 2020, Pattern Recognition
  • Sparse Instance Activation for Real-Time Instance Segmentation, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Diversity Transfer Network for Few-Shot Learning, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction, 2022, arXiv (Cornell University)

Best Publications

  • Conditional Random Fields as Recurrent Neural Networks

    Shuai Zheng;Sadeep Jayasumana;Bernardino Romera-Paredes;Vibhav Vineet

  • CCNet: Criss-Cross Attention for Semantic Segmentation

    Zilong Huang;Xinggang Wang;Lichao Huang;Chang Huang

  • The Visual Object Tracking VOT2017 Challenge Results

    Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg

  • The Visual Object Tracking VOT2015 Challenge Results

    Matej Kristan;Jiri Matas;Ale Leonardis;Michael Felsberg

  • CNN-RNN: A Unified Framework for Multi-label Image Classification

    Jiang Wang;Yi Yang;Junhua Mao;Zhiheng Huang

  • Mask Scoring R-CNN

    Zhaojin Huang;Lichao Huang;Yongchao Gong;Chang Huang

  • Learning from massive noisy labeled data for image classification

    Tong Xiao;Tian Xia;Yi Yang;Chang Huang

  • Learning to associate: HybridBoosted multi-target tracker for crowded scene

    Yuan Li;Chang Huang;Ram Nevatia

  • Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review

    Chang Huang;Yun Chen;Shiqiang Zhang;Jianping Wu

  • Robust Object Tracking by Hierarchical Association of Detection Responses

    Chang Huang;Bo Wu;Ramakant Nevatia

  • Fast rotation invariant multi-view face detection based on real Adaboost

    Bo Wu;Haizhou Ai;Chang Huang;Shihong Lao

  • High-Performance Rotation Invariant Multiview Face Detection

    Chang Huang;Haizhou Ai;Yuan Li;Shihong Lao

  • Deep multiple instance learning for image classification and auto-annotation

    Jiajun Wu;Yinan Yu;Chang Huang;Kai Yu

  • Look and Think Twice: Capturing Top-Down Visual Attention with Feedback Convolutional Neural Networks

    Chunshui Cao;Xianming Liu;Yi Yang;Yinan Yu

  • Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-Identification

    Cheng Wang;Qian Zhang;Chang Huang;Wenyu Liu

  • Multi-target tracking by on-line learned discriminative appearance models

    Cheng-Hao Kuo;Chang Huang;Ramakant Nevatia

  • Unsupervised Domain Adaptive Re-Identification: Theory and Practice

    Liangchen Song;Cheng Wang;Lefei Zhang;Bo Du

  • Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas

    Kaifang Shi;Chang Huang;Bailang Yu;Bing Yin

  • Beyond spatial pyramids: Receptive field learning for pooled image features

    Yangqing Jia;Chang Huang;Trevor Darrell

  • Vector boosting for rotation invariant multi-view face detection

    Chang Huang;Haizhou Ai;Yuan Li;Shihong Lao

  • Targeting Ultimate Accuracy: Face Recognition via Deep Embedding

    Jingtuo Liu;Yafeng Deng;Tao Bai;Chang Huang

  • Detecting spatiotemporal dynamics of global electric power consumption using DMSP-OLS nighttime stable light data

    Kaifang Shi;Kaifang Shi;Yun Chen;Bailang Yu;Tingbao Xu

  • Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the County Level in China

    Bailang Yu;Kaifang Shi;Yingjie Hu;Chang Huang

  • Text Flow: A Unified Text Detection System in Natural Scene Images

    Shangxuan Tian;Yifeng Pan;Chang Huang;Shijian Lu

  • Sparse Instance Activation for Real-Time Instance Segmentation

    Unknown

Frequent Co-Authors

Haizhou Ai
Haizhou Ai Tsinghua University
Xinggang Wang
Xinggang Wang Huazhong University of Science and Technology
Shihong Lao
Shihong Lao SenseTime
Wenyu Liu
Wenyu Liu Huazhong University of Science and Technology
Wei Xu
Wei Xu Horizon Robotics Inc.
Junliang Xing
Junliang Xing Tsinghua University
Ramakant Nevatia
Ramakant Nevatia University of Southern California
Shiming Xiang
Shiming Xiang Chinese Academy of Sciences
Philip H. S. Torr
Philip H. S. Torr University of Oxford
Lefei Zhang
Lefei Zhang Wuhan University

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