Fisher Yu is a postdoctoral researcher at the University of California, Berkeley, working with Trevor Darrell. He pursued his Ph.D. degree at Princeton University, advised by Thomas Funkhouser. During his Ph.D. study, he also collaborated extensively with Vladlen Koltun at Intel and Jianxiong Xiao at Princeton University. He obtained his bachelor degree from the University of Michigan, Ann Arbor. His research interest lies in computer vision systems, including unified representation frameworks, 3D dynamic scene analysis, and software system for interactive data processing.

C.V. Google Scholar Research Statement Teaching Statement

Email i AT yf.io
Office Cory Hall 307, Berkeley, CA, 94720

Xin Wang, Fisher Yu, Ruth Wang, Trevor Darrell, Joseph E. Gonzalez
TAFE-Net: Task-Aware Feature Embeddings for Efficient Learning and Inference
In Submission, 2019
Xinlei Pan, Xiangyu Chen, Qi-Zhi Cai, John F. Canny, Fisher Yu
Semantic Predictive Control for Interpretable and Efficient Policy Learning
In Submission, 2019
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
In Submission, 2019
Zhichao Yin, Trevor Darrell, Fisher Yu
Hierarchical Discrete Distribution Decomposition for Match Density Estimation
In Submission, 2019
Hang Gao, Huazhe Xu, Qi-Zhi Cai, Ruth Wang, Fisher Yu, Trevor Darrell
Disentangling Propagation and Generation for Video Prediction
In Submission, 2019
Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell
Few-shot Object Detection via Feature Reweighting
In Submission, 2019
Dequan Wang, Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell
Deep Object Centric Policies for Autonomous Driving
In Submission, 2019
Xin Wang, Fisher Yu, Zi-Yi Dou, Joseph E. Gonzalez
SkipNet: Learning Dynamic Routing in Convolutional Networks
European Conference on Computer Vision, 2018
Chaowei Xiao, Ruizhi Deng, Bo Li, Fisher Yu, Mingyan Liu, Dawn Song
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
European Conference on Computer Vision, 2018
Fisher Yu, Wenqi Xian, Yingying Chen, Fangchen Liu, Mike Liao, Vashisht Madhavan, Trevor Darrell
BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling
arXiv, 2018
Fisher Yu, Dequan Wang, Evan Shelhamer, Trevor Darrell
Deep Layer Aggregation
Computer Vision and Pattern Recognition, 2018
Wenqi Xian, Patsorn Sangkloy, Varun Agrawal, Amit Raj, Jingwan Lu, Chen Fang, Fisher Yu and James Hays
TextureGAN: Controlling Deep Image Synthesis with Texture Patches
Computer Vision and Pattern Recognition, 2018
Huiwen Chang, Jingwan Lu, Fisher Yu and Adam Finkelstein
PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup
Computer Vision and Pattern Recognition, 2018
Xin Wang, Yujia Luo, Daniel Crankshaw, Alexey Tumanov, Fisher Yu, Joseph E. Gonzalez
IDK Cascades: Fast Deep Learning by Learning not to Overthink
Conference on Uncertainty in Artificial Intelligence, 2018
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
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

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.