CVPR 2020에서 구글
2020년 6월 15일 (월) - 구글 AI 리서치 블로그
이번 주에는 메인 컨퍼런스, 워크샵 및 자습서들로 구성된 연례 컴퓨터 비전 행사인 Computer Vision and Pattern Recognition(CVPR 2020)에 대한 완전 가상 2020 회의가 시작됩니다. 컴퓨터 비전 연구의 리더이자 후원자 수준의 가상 스폰서인 Google은 CVPR 2020에서 여러 워크샵/자습서의 구성 및 참여와 함께 거의 70권의 출판물을 받아 볼 수 있습니다.
올해 CVPR에 참여하는 경우 가상 부스를 방문하여 다양한 머신 인식(machine perception) 영역에 적용되는 최신 머신러닝 기술을 활용하는 차세대 지능형 시스템을 위해 Google이 적극적으로 추구하는 사항에 대해 알아보십시오.
아래 목록에서 CVPR 2020에 발표 된 연구에 대해 자세히 알아볼 수도 있습니다 (Google 제휴사는 굵은색 표시됨).
조직 위원회
일반 의장들: Terry Boult, Gerard Medioni, Ramin Zabih
프로그램 의장들: Ce Liu, Greg Mori, Kate Saenko, Silvio Savarese
Workshop Chairs: Tal Hassner, Tali Dekel
Website Chairs: Tianfan Xue, Tian Lan
Technical Chair: Daniel Vlasic
Area Chairs include: Alexander Toshev, Alexey Dosovitskiy, Boqing Gong, Caroline Pantofaru, Chen Sun, Deqing Sun, Dilip Krishnan, Feng Yang, Liang-Chieh Chen, Michael Rubinstein, Rodrigo Benenson, Timnit Gebru, Thomas Funkhouser, Varun Jampani, Vittorio Ferrari, William Freeman
구두 발표자료들
Evolving Losses for Unsupervised Video Representation Learning
AJ Piergiovanni, Anelia Angelova, Michael Ryoo
CvxNet: Learnable Convex Decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz, Geoffrey Hinton, Andrea Tagliasacchi
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise
Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurélien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Sheng Zhao, Shuyang Chen, Yu Zhang, Jon Shlens, Zhifeng Chen, Dragomir Anguelov
Deep Implicit Volume Compression
Saurabh Singh, Danhang Tang, Cem Keskin, Philip Chou, Christian Haene, Mingsong Dou, Sean Fanello, Jonathan Taylor, Andrea Tagliasacchi, Philip Davidson, Yinda Zhang, Onur Guleryuz, Shahram Izadi, Sofien Bouaziz
Dongdong Wan, Yandong Li, Liqiang Wang, and Boqing Gong
Google Landmarks Dataset v2 - A Large-Scale Benchmark for Instance-Level Recognition and Retrieval (see the blog post)
Tobias Weyand, Andre Araujo, Jack Sim, Bingyi Cao
CycleISP: Real Image Restoration via Improved Data Synthesis
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao
Dynamic Graph Message Passing Networks
Li Zhang, Dan Xu, Anurag Arnab, Philip Torr
Local Deep Implicit Functions for 3D Shape
Kyle Genova, Forrester Cole, Avneesh Sud, Aaron Sarna, Thomas Funkhouser
GHUM & GHUML: Generative 3D Human Shape and Articulated Pose Models
Hongyi Xu, Eduard Gabriel Bazavan, Andrei Zanfir, William Freeman, Rahul Sukthankar, Cristian Sminchisescu
Search to Distill: Pearls are Everywhere but not the Eyes
Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
Semantic Pyramid for Image Generation
Assaf Shocher, Yossi Gandelsman, Inbar Mosseri, Michal Yarom, Michal Irani, William Freeman, Tali Dekel
Flow Contrastive Estimation of Energy-Based Models
Ruiqi Gao, Erik Nijkamp, Diederik Kingma, Zhen Xu, Andrew Dai, Ying Nian Wu
Muhammad Abdullah Jamal, Matthew Brown, Ming-Hsuan Yang, Liqiang Wang, Boqing Gong
Category-Level Articulated Object Pose Estimation
Xiaolong Li, He Wang, Li Yi, Leonidas Guibas, Amos Abbott, Shuran Song
AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Li Yi, Leonidas Guibas, Hao Zhang
SpeedNet: Learning the Speediness in Videos
Sagie Benaim, Ariel Ephrat, Oran Lang, Inbar Mosseri, William Freeman, Michael Rubinstein, Michal Irani, Tali Dekel
BSP-Net: Generating Compact Meshes via Binary Space Partitioning
Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
SAPIEN: A SimulAted Part-based Interactive ENvironment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel Chang, Leonidas Guibas, Hao Su
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar
Saurabh Singh, Shankar Krishnan
RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real
Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari
Open Compound Domain Adaptation
Ziwei Liu, Zhongqi Miao, Xingang Pan, Xiaohang Zhan, Dahua Lin, Stella X.Yu, and Boqing Gong
Posters
Single-view view synthesis with multiplane images
Richard Tucker, Noah Snavely
Adversarial Examples Improve Image Recognition
Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan Yuille, Quoc V. Le
Adversarial Texture Optimization from RGB-D Scans
Jingwei Huang, Justus Thies, Angela Dai, Abhijit Kundu, Chiyu “Max” Jiang,Leonidas Guibas, Matthias Niessner, Thomas Funkhouser
Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline
Yu-Lun Liu, Wei-Sheng Lai, Yu-Sheng Chen, Yi-Lung Kao, Ming-Hsuan Yang,Yung-Yu Chuang, Jia-Bin Huang
Collaborative Distillation for Ultra-Resolution Universal Style Transfer
Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan Yang
Charles Herrmann, Richard Strong Bowen, Neal Wadhwa, Rahul Garg, Qiurui He, Jonathan T. Barron, Ramin Zabih
Multi-Scale Boosted Dehazing Network with Dense Feature Fusion
Hang Dong, Jinshan Pan, Lei Xiang, Zhe Hu, Xinyi Zhang, Fei Wang, Ming-Hsuan Yang
Composing Good Shots by Exploiting Mutual Relations
Debang Li, Junge Zhang, Kaiqi Huang, Ming-Hsuan Yang
PatchVAE: Learning Local Latent Codes for Recognition
Kamal Gupta, Saurabh Singh, Abhinav Shrivastava
Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool
Konstantinos Rematas, Vittorio Ferrari
Local Implicit Grid Representations for 3D Scenes
Chiyu “Max” Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Niessner, Thomas Funkhouser
Large Scale Video Representation Learning via Relational Graph Clustering
Hyodong Lee, Joonseok Lee, Joe Yue-Hei Ng, Apostol (Paul) Natsev
Deep Homography Estimation for Dynamic Scenes
Hoang Le, Feng Liu, Shu Zhang, Aseem Agarwala
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds
Albert Pumarola, Stefan Popov, Francesc Moreno-Noguer, Vittorio Ferrari
Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination
Pratul Srinivasan, Ben Mildenhall, Matthew Tancik, Jonathan T. Barron, Richard Tucker, Noah Snavely
Scale-space flow for end-to-end optimized video compression
Eirikur Agustsson, David Minnen, Nick Johnston, Johannes Ballé, Sung Jin Hwang, George Toderici
StructEdit: Learning Structural Shape Variations
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy Mitra, Leonidas Guibas
3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation
Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe, Matthias Niessner
Sequential mastery of multiple tasks: Networks naturally learn to learn and forget to forget
Guy Davidson, Michael C. Mozer
Distilling Effective Supervision from Severe Label Noise
Zizhao Zhang, Han Zhang, Sercan Ö. Arik, Honglak Lee, Tomas Pfister
ViewAL: Active Learning With Viewpoint Entropy for Semantic Segmentation
Yawar Siddiqui, Julien Valentin, Matthias Niessner
Attribution in Scale and Space
Shawn Xu, Subhashini Venugopalan, Mukund Sundararajan
Weakly-Supervised Semantic Segmentation via Sub-category Exploration
Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, Ming-Hsuan Yang
Speech2Action: Cross-modal Supervision for Action Recognition
Arsha Nagrani, Chen Sun, David Ross, Rahul Sukthankar, Cordelia Schmid, Andrew Zisserman
Counting Out Time: Class Agnostic Video Repetition Counting in the Wild
Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, Andrew Zisserman
The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction
Junwei Liang, Lu Jiang, Kevin Murphy, Ting Yu, Alexander Hauptmann
Self-training with Noisy Student improves ImageNet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy, Quoc V. Le
EfficientDet: Scalable and Efficient Object Detection (see the blog post)
Mingxing Tan, Ruoming Pang, Quoc Le
ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning
Weiwei Sun, Wei Jiang, Eduard Trulls, Andrea Tagliasacchi, Kwang Moo Yi
VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation
Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Cordelia Schmid, Congcong Li
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc Le, Xiaodan Song
KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects
Xingyu Liu, Rico Jonschkowski, Anelia Angelova, Kurt Konolige
Structured Multi-Hashing for Model Compression
Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel A. Carreira-Perpinan
DOPS: Learning to Detect 3D Objects and Predict their 3D Shapes
Mahyar Najibi, Guangda Lai, Abhijit Kundu, Zhichao Lu, Vivek Rathod, Tom Funkhouser, Caroline Pantofaru, David Ross, Larry Davis, Alireza Fathi
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
Bowen Cheng, Maxwell Collins, Yukun Zhu, Ting Liu, Thomas S. Huang, Hartwig Adam, Liang-Chieh Chen
Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection
Sara Beery, Guanhang Wu, Vivek Rathod, Ronny Votel, Jonathan Huang
Distortion Agnostic Deep Watermarking
Xiyang Luo, Ruohan Zhan, Huiwen Chang, Feng Yang, Peyman Milanfar
Can weight sharing outperform random architecture search? An investigation with TuNAS
Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc Le
GIFnets: Differentiable GIF Encoding Framework
Innfarn Yoo, Xiyang Luo, Yilin Wang, Feng Yang, Peyman Milanfar
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models
Giannis Daras, Augustus Odena, Han Zhang, Alex Dimakis
Erich Elsen, Marat Dukhan, Trevor Gale, Karen Simonyan
RetinaTrack: Online Single Stage Joint Detection and Tracking
Zhichao Lu, Vivek Rathod, Ronny Votel, Jonathan Huang
Learning to See Through Obstructions
Yu-Lun Liu, Wei-Sheng Lai, Ming-Hsuan Yang,Yung-Yu Chuang, Jia-Bin Huang
Self-Supervised Learning of Video-Induced Visual Invariances
Michael Tschannen, Josip Djolonga, Marvin Ritter, Aravindh Mahendran, Neil Houlsby, Sylvain Gelly, Mario Lucic
Workshops
3rd Workshop and Challenge on Learned Image Compression
Organizers include: George Toderici, Eirikur Agustsson, Lucas Theis, Johannes Ballé, Nick Johnston
CLVISION 1st Workshop on Continual Learning in Computer Vision
Organizers include: Zhiyuan (Brett) Chen, Marc Pickett
Organizers include: Alexander Toshev, Jie Tan, Aleksandra Faust, Anelia Angelova
Organizers include: Zhen Li, Jim Yuan
Talk: “Sky Optimization: Semantically aware image processing of skies in low-light photography”
Orly Liba, Longqi Cai, Yun-Ta Tsai, Elad Eban, Yair Movshovitz-Attias, Yael Pritch, Huizhong Chen, Jonathan Barron
The End-of-End-to-End A Video Understanding Pentathlon
Organizers include: Rahul Sukthankar
4th Workshop on Media Forensics
Organizers include: Christoph Bregler
4th Workshop on Visual Understanding by Learning from Web Data
Organizers include: Jesse Berent, Rahul Sukthankar
Organizers include: Deqing Sun, Lu Jiang, Weilong Yang
Fourth Workshop on Computer Vision for AR/VR
Organizers include: Sofien Bouaziz
Low-Power Computer Vision Competition (LPCVC)
Organizers include: Bo Chen, Andrew Howard, Jaeyoun Kim
Organizers include: William Freeman
Workshop on Efficient Deep Learning for Computer Vision
Organizers include: Pete Warden
Extreme classification in computer vision
Organizers include: Ramin Zabih, Zhen Li
Image Matching: Local Features and Beyond (see the blog post)
Organizers include: Eduard Trulls
The DAVIS Challenge on Video Object Segmentation
Organizers include: Alberto Montes, Jordi Pont-Tuset, Kevis-Kokitsi Maninis
2nd Workshop on Precognition: Seeing through the Future
Organizers include: Utsav Prabhu
Computational Cameras and Displays (CCD)
Talk: Orly Liba
2nd Workshop on Learning from Unlabeled Videos (LUV)
Organizers include:Honglak Lee, Rahul Sukthankar
7th Workshop on Fine Grained Visual Categorization (FGVC7) (see the blog post)
Organizers include: Christine Kaeser-Chen, Serge Belongie
Language & Vision with applications to Video Understanding
Organizers include: Lu Jiang
Neural Architecture Search and Beyond for Representation Learning
Organizers include: Barret Zoph
자습서들
Disentangled 3D Representations for Relightable Performance Capture of Humans
Organizers include: Sean Fanello, Christoph Rhemann, Jonathan Taylor, Sofien Bouaziz, Adarsh Kowdle, Rohit Pandey, Sergio Orts-Escolano, Paul Debevec, Shahram Izadi
Learning Representations via Graph-Structured Networks
Organizers include:Chen Sun, Ming-Hsuan Yang
Novel View Synthesis: From Depth-Based Warping to Multi-Plane Images and Beyond
Organizers include:Varun Jampani
Talks by:Vittorio Ferrari, Bill Freeman, Jordi Pont-Tuset
Organizers include:Ricardo Martin-Brualla, Rohit K. Pandey, Sean Fanello,Maneesh Agrawala, Dan B. Goldman
Fairness Accountability Transparency and Ethics and Computer Vision
Organizers: Timnit Gebru, Emily Denton
원본 제목: CVPR 2020에서 구글(Google at CVPR 2020)
게시자 : Emily Knapp, 프로그램 관리자 및 Benjamin Hütteroth, 프로그램 전문가
원본 링크: https://ai.googleblog.com/2020/06/google-at-cvpr-2020.html
CVPR 2020 : http://cvpr2020.thecvf.com
이 블로그는 2020년 6월 15일(월), Google AI 리서치 블로그 기사를 영한 번역한 것입니다. 또한 이 번역 글은 정보 공유 목적으로만 작성했으므로 어떠한 상업용으로 사용할 수 없으며, 원본 저작물 모두 구글에게 저작권이 있음을 알려 드립니다. (First Draft Version)
