I am an Assistant Professor at ETH Zürich in Switzerland. I obtained my Ph.D. degree from Princeton University and became a postdoctoral researcher at UC Berkeley afterwards. I direct the Visual Intelligence and Systems (cv.ethz.ch) Group in the Computer Vision Lab. My goal is to build perceptual systems capable of performing complex tasks in complex environments. My research is at the junction of machine learning, computer vision, and robotics. I currently work on closing the loop between vision and action. More info about our recent works is at vis.xyz. You can follow me on Twitter, LinkedIn or Zhihu for updates and news.

I am currently looking for students with strong research records in computer science, electrical engineering, or mechanical engineering to join my group as Ph.D. students, postdoctoral researchers, or research interns. Please check our group page for the details: https://cv.ethz.ch/the-group.html.

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Selected Publications

You can find the full list on our group publication page and Google Scholar.

	Jiangmiao Pang, Linlu Qiu, Xia Li, Haofeng Chen, Qi Li, Trevor Darrell, Fisher Yu Quasi-Dense Similarity Learning for Multiple Object Tracking Computer Vision and Pattern Recognition, 2021 Webpage Paper Code
	Jinkun Cao, Xin Wang, Trevor Darrell, Fisher Yu Instance-Aware Predictive Navigation in Multi-Agent Environments International Conference on Robotics and Automation, 2021 Webpage Paper Code
	Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, Trevor Darrell BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning Computer Vision and Pattern Recognition, 2020 Webpage Paper Data Code Scalabel Labeling Tool
	Xin Wang*, Thomas E. Huang*, Trevor Darrell, Joseph E. Gonzalez, Fisher Yu Frustratingly Simple Few-Shot Object Detection International Conference on Machine Learning, 2020 Webpage Paper Code
	Hou-Ning Hu, Qi-Zhi Cai, Dequan Wang, Ji Lin, Min Sun, Philipp Krähenbühl, Trevor Darrell, Fisher Yu Joint Monocular 3D Vehicle Detection and Tracking International Conference in Computer Vision, 2019 Webpage Paper Code
	Zhichao Yin, Trevor Darrell, Fisher Yu Hierarchical Discrete Distribution Decomposition for Match Density Estimation Computer Vision and Pattern Recognition, 2019 Webpage Paper Code
	Xin Wang, Fisher Yu, Zi-Yi Dou, Joseph E. Gonzalez SkipNet: Learning Dynamic Routing in Convolutional Networks European Conference on Computer Vision, 2018 Webpage Paper Code
	Fisher Yu, Dequan Wang, Evan Shelhamer, Trevor Darrell Deep Layer Aggregation Computer Vision and Pattern Recognition, 2018 Webpage Paper
	Fisher Yu, Vladlen Koltun and Thomas Funkhouser Dilated Residual Networks Computer Vision and Pattern Recognition, 2017 Webpage Paper Code
	Huazhe Xu, Yang Gao, Fisher Yu and Trevor Darrell End-to-end Learning of Driving Models from Large-scale Video Datasets Computer Vision and Pattern Recognition, 2017 Webpage Paper
	Fisher Yu and Vladlen Koltun Multi-Scale Context Aggregation by Dilated Convolutions International Conference on Learning Representations, 2016 Webpage Paper Code
	Fisher Yu, Jianxiong Xiao and Thomas Funkhouser Semantic Alignment of LiDAR Data at City Scale Computer Vision and Pattern Recognition, 2015 Webpage Paper
	Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser and Jianxiong Xiao LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop arXiv:1506.03365 cs.CV, 2015 Webpage Paper Challenge
	Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, Fisher Yu ShapeNet: An Information-Rich 3D Model Repository arXiv:1512.03012 cs.GR, 2015 Webpage Paper
	Fisher Yu and David Gallup 3D Reconstruction from Accidental Motion Computer Vision and Pattern Recognition, 2014 Webpage Paper Video Youtube code Bibtex

Services

• Organizer of Workshop on Autonomous Driving at CVPR 2017, 2018, 2019, 2020
• Organizer of Workshop on Machine Learning for Autonomous Driving at NeurIPS 2019
• Organizer of Workshop on Human In the Loop Learning (HILL) at ICML 2019
• Organizer of 3D Deep Learning Workshop at NIPS 2016
• Organizer of Large-scale Scene Understanding Challenge Workshop at CVPR 2016
• Organizer of CVPR 2016 tutorial on 3D Deep Learning with Marvin
• Organizer of Large-scale Scene Understanding Challenge Workshop at CVPR 2015

Tutorials

Here are the slides of the lectures on 3D reconstruction I gave in a seminar course in 2014. These lectures are intended for audience with no background knowledge in this area.