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2025

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Rising Stars

D-Index
53
Citations
38686
World Ranking
237
National Ranking
2

Computer Science

D-Index
56
Citations
39025
World Ranking
3932
National Ranking
87

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Fisher Yu is affiliated with ETH Zurich in Switzerland and has contributed extensively to the fields of Computer Science and Engineering. Their research primarily focuses on computer vision, artificial intelligence, and related subfields such as aerospace and automotive engineering as well as computational mechanics.

Their main areas of study encompass:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Aerospace Engineering
  • Automotive Engineering
  • Computational Mechanics

Yu's research addresses a wide array of topics including:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Advanced Vision and Imaging
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Robotics and Sensor-Based Localization

Their publication record includes papers presented at prestigious venues, illustrating ongoing activity in high-impact conferences and repositories such as:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Repository for Publications and Research Data (ETH Zurich)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Recent publications by Fisher Yu include:

  • "ShapeNet: An Information-Rich 3D Model Repository," 2023, Zenodo (CERN European Organization for Nuclear Research)
  • "RePaint: Inpainting using Denoising Diffusion Probabilistic Models," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Exploring Cross-Image Pixel Contrast for Semantic Segmentation," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Transforming Model Prediction for Tracking," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Generative Cooperative Learning for Unsupervised Video Anomaly Detection," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The scientist collaborates frequently with a network of co-authors, notably including Luc Van Gool, Martin Danelljan, Mattia Segù, Thomas E. Huang, and Yu-Wing Tai. These collaborators share many joint publications, reflecting strong research partnerships mainly in computer vision and related disciplines.

Best Publications

  • Multi-Scale Context Aggregation by Dilated Convolutions

    Fisher Yu;Vladlen Koltun

  • 3D ShapeNets: A deep representation for volumetric shapes

    Zhirong Wu;Shuran Song;Aditya Khosla;Fisher Yu

  • ShapeNet: An Information-Rich 3D Model Repository

    Angel X. Chang;Thomas A. Funkhouser;Leonidas J. Guibas;Pat Hanrahan

  • BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

    Fisher Yu;Haofeng Chen;Xin Wang;Wenqi Xian

  • RePaint: Inpainting using Denoising Diffusion Probabilistic Models

    Unknown

  • LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

    Fisher Yu;Yinda Zhang;Shuran Song;Ari Seff

  • Dilated Residual Networks

    Fisher Yu;Vladlen Koltun;Thomas Funkhouser

  • Deep Layer Aggregation

    Fisher Yu;Dequan Wang;Evan Shelhamer;Trevor Darrell

  • Semantic Scene Completion from a Single Depth Image

    Shuran Song;Fisher Yu;Andy Zeng;Angel X. Chang

  • BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling.

    Fisher Yu;Wenqi Xian;Yingying Chen;Fangchen Liu

  • End-to-End Learning of Driving Models from Large-Scale Video Datasets

    Huazhe Xu;Yang Gao;Fisher Yu;Trevor Darrell

  • FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

    Judy Hoffman;Dequan Wang;Fisher Yu;Trevor Darrell

  • Few-Shot Object Detection via Feature Reweighting

    Bingyi Kang;Zhuang Liu;Xin Wang;Fisher Yu

  • SkipNet: Learning Dynamic Routing in Convolutional Networks

    Xin Wang;Fisher Yu;Zi-Yi Dou;Trevor Darrell

  • Scribbler: Controlling Deep Image Synthesis with Sketch and Color

    Patsorn Sangkloy;Jingwan Lu;Chen Fang;Fisher Yu

  • Exploring Cross-Image Pixel Contrast for Semantic Segmentation

    Wenguan Wang;Tianfei Zhou;Fisher Yu;Jifeng Dai

  • Transforming Model Prediction for Tracking

    Unknown

  • Quasi-Dense Similarity Learning for Multiple Object Tracking

    Jiangmiao Pang;Linlu Qiu;Xia Li;Haofeng Chen

  • TextureGAN: Controlling Deep Image Synthesis with Texture Patches

    Wenqi Xian;Patsorn Sangkloy;Varun Agrawal;Amit Raj

  • Scaling Vision Transformers to 22 Billion Parameters

    Unknown

  • Frustratingly Simple Few-Shot Object Detection

    Xin Wang;Thomas Huang;Joseph Gonzalez;Trevor Darrell

  • PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup

    Huiwen Chang;Jingwan Lu;Fisher Yu;Adam Finkelstein

  • Hierarchical Discrete Distribution Decomposition for Match Density Estimation

    Zhichao Yin;Trevor Darrell;Fisher Yu

Frequent Co-Authors

Trevor Darrell
Trevor Darrell University of California, Berkeley
Joseph E. Gonzalez
Joseph E. Gonzalez University of California, Berkeley
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Thomas Funkhouser
Thomas Funkhouser Google (United States)
Shuran Song
Shuran Song Stanford University
Manolis Savva
Manolis Savva Simon Fraser University
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Jianxiong Xiao
Jianxiong Xiao AutoX, Inc.
Vladlen Koltun
Vladlen Koltun Apple (United States)

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