World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
76
Citations
30709
World Ranking
1318
National Ranking
695

Overview

Zhe Lin is a researcher affiliated with Adobe Systems in the United States specializing in computer science, with a particular focus on computer vision and artificial intelligence. Their body of work encompasses a range of topics within these fields, including generative adversarial networks, multimodal machine learning applications, and advanced image and video retrieval techniques.

The primary fields of study for Zhe Lin include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Media Technology
  • Cognitive Neuroscience

The main topics covered in their research involve:

  • Generative Adversarial Networks and Image Synthesis
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Advanced Vision and Imaging
  • Advanced Image Processing Techniques
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning

Zhe Lin's recent publications feature research on image inpainting, semantic segmentation, and vision transformers. Notable recent papers include:

  • "MAT: Mask-Aware Transformer for Large Hole Image Inpainting," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Real-Time Semantic Segmentation With Fast Attention," 2020, IEEE Robotics and Automation Letters
  • "Lite Vision Transformer with Enhanced Self-Attention," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation," 2021, arXiv (Cornell University)

Zhe Lin frequently collaborates with other researchers. Among the most common co-authors are Jianming Zhang, Jason Kuen, Scott Cohen, Eli Shechtman, and Jiaya Jia.

They have contributed extensively to various publication venues, with the most frequent being:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence

The volume of publications across these venues and the diversity of research topics illustrate Zhe Lin's active participation in advancing computer vision and related fields.

Best Publications

  • Generative Image Inpainting with Contextual Attention

    Jiahui Yu;Zhe Lin;Jimei Yang;Xiaohui Shen

  • A convolutional neural network cascade for face detection

    Haoxiang Li;Zhe Lin;Xiaohui Shen;Jonathan Brandt

  • Free-Form Image Inpainting With Gated Convolution

    Jiahui Yu;Zhe Lin;Jimei Yang;Xiaohui Shen

  • Label Consistent K-SVD: Learning a Discriminative Dictionary for Recognition

    Zhuolin Jiang;Zhe Lin;L. S. Davis

  • Interactive facial feature localization

    Vuong Le;Jonathan Brandt;Zhe Lin;Lubomir Bourdev

  • Coupled Dictionary Training for Image Super-Resolution

    Jianchao Yang;Zhaowen Wang;Zhe Lin;S. Cohen

  • High-Resolution Image Inpainting Using Multi-scale Neural Patch Synthesis

    Chao Yang;Xin Lu;Zhe Lin;Eli Shechtman

  • Learning a discriminative dictionary for sparse coding via label consistent K-SVD

    Zhuolin Jiang;Zhe Lin;Larry S. Davis

  • Top-Down Neural Attention by Excitation Backprop

    Jianming Zhang;Sarah Adel Bargal;Zhe Lin;Jonathan Brandt

  • MAttNet: Modular Attention Network for Referring Expression Comprehension

    Licheng Yu;Zhe Lin;Xiaohui Shen;Jimei Yang

  • Top-Down Neural Attention by Excitation Backprop

    Jianming Zhang;Zhe L. Lin;Jonathan Brandt;Xiaohui Shen

  • Towards unified depth and semantic prediction from a single image

    Peng Wang;Xiaohui Shen;Zhe Lin;Scott Cohen

  • Photo Aesthetics Ranking Network with Attributes and Content Adaptation

    Shu Kong;Xiaohui Shen;Zhe L. Lin;Radomír Mech

  • Minimum Barrier Salient Object Detection at 80 FPS

    Jianming Zhang;Stan Sclaroff;Zhe Lin;Xiaohui Shen

  • RAPID: Rating Pictorial Aesthetics using Deep Learning

    Xin Lu;Zhe Lin;Hailin Jin;Jianchao Yang

  • Recognizing actions by shape-motion prototype trees

    Zhe Lin;Zhuolin Jiang;Larry S. Davis

  • Foreground-Aware Image Inpainting

    Wei Xiong;Jiahui Yu;Zhe Lin;Jimei Yang

  • Fast Image Super-Resolution Based on In-Place Example Regression

    Jianchao Yang;Zhe Lin;Scott Cohen

  • Deep Multi-patch Aggregation Network for Image Style, Aesthetics, and Quality Estimation

    Xin Lu;Zhe Lin;Xiaohui Shen;Radomir Mech

  • Image Super-Resolution by Neural Texture Transfer

    Zhifei Zhang;Zhaowen Wang;Zhe Lin;Hairong Qi

  • Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching

    Zhe Lin;L.S. Davis

  • Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers

    Jianbo Ye;Xin Lu;Zhe L. Lin;James Z. Wang

Frequent Co-Authors

Xiaohui Shen
Xiaohui Shen ByteDance
Jonathan Brandt
Jonathan Brandt Adobe Systems (United States)
Radomir Mech
Radomir Mech Adobe Systems (United States)
Hailin Jin
Hailin Jin Adobe Systems (United States)
Scott Cohen
Scott Cohen Adobe Systems (United States)
Jianchao Yang
Jianchao Yang ByteDance
Jimei Yang
Jimei Yang Adobe Systems (United States)
Brian Price
Brian Price Adobe Systems (United States)
Larry S. Davis
Larry S. Davis University of Maryland, College Park
Kalyan Sunkavalli
Kalyan Sunkavalli Adobe Systems (United States)

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