About
Fisher Yu is a postdoctoral researcher at UC 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. He obtained his bachelor degree from University of Michigan, Ann Arbor. His research interest lies in representation learning 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
Publications
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SkipNet: Learning Dynamic Routing in Convolutional Networks
European Conference on Computer Vision,
2018
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Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
European Conference on Computer Vision,
2018
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Deep Layer Aggregation
Computer Vision and Pattern Recognition,
2018
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TextureGAN: Controlling Deep Image Synthesis with Texture Patches
Computer Vision and Pattern Recognition,
2018
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MakeupGAN: Makeup Transfer via Cycle-Consistent Adversarial Networks
Computer Vision and Pattern Recognition,
2018
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IDK Cascades: Fast Deep Learning by Learning not to Overthink
Conference on Uncertainty in Artificial Intelligence,
2018
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Dilated Residual Networks
Computer Vision and Pattern Recognition,
2017
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Semantic Scene Completion from a Single Depth Image
Computer Vision and Pattern Recognition,
2017
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End-to-end Learning of Driving Models from Large-scale Video Datasets
Computer Vision and Pattern Recognition,
2017
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Scribbler: Controlling Deep Image Synthesis with Sketch and Color
Computer Vision and Pattern Recognition,
2017
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Interactive 3D Modeling with a Generative Adversarial Network
International Conference on 3D Vision,
2017
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Multi-Scale Context Aggregation by Dilated Convolutions
International Conference on Learning Representations,
2016
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Automatic Triage for a Photo Series
ACM Transactions on Graphics (Proc. SIGGRAPH),
2016
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SHREC’16 Track`: Large-Scale 3D Shape Retrieval from ShapeNet Core55
EuroGraphics SHREC2016 Workshop Report,
2016
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Semantic Alignment of LiDAR Data at City Scale
Computer Vision and Pattern Recognition,
2015
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LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans
in the Loop
arXiv:1506.03365 cs.CV,
2015
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ShapeNet: An Information-Rich 3D Model Repository
arXiv:1512.03012 cs.GR,
2015
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3D ShapeNets: A Deep Representation for Volumetric Shape Modeling
Computer Vision and Pattern Recognition,
2015
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3D Reconstruction from Accidental Motion
Computer Vision and Pattern Recognition,
2014
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HelpingHand: Example-based Stroke Stylization
ACM Transactions on Graphics (Proc. SIGGRAPH),
2012
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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
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Services
- Organizer of Workshop on Autonomous Driving at CVPR 2018
- Organizer of Workshop on Autonomous Driving Challenges at CVPR 2017
- 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