About

Fisher Yu is a researcher in University of California, Berkeley, advised by Prof. Trevor Darrell. He pursued Ph.D. degree in Princeton University, advised by Prof. Thomas Funkhouser and Prof. Jianxiong Xiao. Before that, he received BSE and MSE from University of Michigan. His research interest is learning universal representation for image recognition, Internet-scale visual understanding and vision based autonomous driving system.

Contact

The best way to reach me is to send email to i AT yf.io

News

2017-02 Four papers are accepted by CVPR 2017.
2016-12 Our workshop on Autonomous Driving Challenge is accepted by CVPR 2017.
2016-12 Our workshop on Large-Scale Scene Understanding Challenge is accepted by CVPR 2017.

Publications

Fisher Yu, Vladlen Koltun and Thomas Funkhouser
Dilated Residual Networks
Computer Vision and Pattern Recognition, 2017
Shuran Song, Fisher Yu, Andy Zeng, Angel X. Chang, Manolis Savva and Thomas Funkhouser
Semantic Scene Completion from a Single Depth Image
Computer Vision and Pattern Recognition, 2017
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
Patsorn Sangkloy, Jingwan Lu, Chen Fang, Fisher Yu and James Hays
Scribbler: Controlling Deep Image Synthesis with Sketch and Color
Computer Vision and Pattern Recognition, 2017
Jerry Liu, Fisher Yu and Thomas Funkhouser
Interactive 3D Modeling with a Generative Adversarial Network
International Conference on 3D Vision, 2017
Wenqi Xian, Patsorn Sangkloy, Jingwan Lu, Chen Fang, Fisher Yu and James Hays
TextureGAN: Controlling Deep Image Synthesis with Texture Patches
arXiv:1706.02823 cs.CV, 2017
Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, Joseph E. Gonzalez
IDK Cascades: Fast Deep Learning by Learning not to Overthink
arXiv:1706.00885 cs.CV, 2017
Judy Hoffman, Dequan Wang, Fisher Yu and Trevor Darrell
FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation
arXiv:1612.02649 cs.CV, 2016
Fisher Yu and Vladlen Koltun
Multi-Scale Context Aggregation by Dilated Convolutions
International Conference on Learning Representations, 2016
Huiwen Chang, Fisher Yu, Jue wang, Douglas Ashley and Adam Finkelstein
Automatic Triage for a Photo Series
ACM Transactions on Graphics (Proc. SIGGRAPH), 2016
Manolis Savva, Fisher Yu, Hao Su, et al.
SHREC’16 Track`: Large-Scale 3D Shape Retrieval from ShapeNet Core55
EuroGraphics SHREC2016 Workshop Report, 2016
Fisher Yu, Jianxiong Xiao and Thomas Funkhouser
Semantic Alignment of LiDAR Data at City Scale
Computer Vision and Pattern Recognition, 2015
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
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
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang and Jianxiong Xiao
3D ShapeNets: A Deep Representation for Volumetric Shape Modeling
Computer Vision and Pattern Recognition, 2015
Fisher Yu and David Gallup
3D Reconstruction from Accidental Motion
Computer Vision and Pattern Recognition, 2014
Jingwan Lu, Fisher Yu, Adam Finkelstein and Stephen DiVerdi
HelpingHand: Example-based Stroke Stylization
ACM Transactions on Graphics (Proc. SIGGRAPH), 2012
John P. Boyd and Fisher Yu
Comparing Seven Spectral Methods for Interpolation and for Solving the Poisson Equation in a Disk: Zernike Polynomials, Logan-Shepp Ridge Polynomials, Chebyshev-Fourier Series, Cylindrical Robert Functions, Bessel-Fourier Expansions, Square-to-Disk Conformal Mapping and Radial Basis Functions
Journal of Computational Physics, Volume 230, Issue 4, 2011

Services

Tutorials

Here are the resources about the lectures on 3D reconstruction I gave in a seminar course instructed by Prof. Jianxiong Xiao. These lectures are intended for audience with no background knowledge in this area.