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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 SiQin CaoSanjiv 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 CaineVijay VasudevanWei HanJiquan Ngiam, Hang Zhao, Aleksei Timofeev‎, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi‎, Sheng Zhao, Shuyang Chen, Yu Zhang, Jon ShlensZhifeng 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 


Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model

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 KingmaZhen XuAndrew Dai, Ying Nian Wu


Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from A Domain Adaptation Perspective

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 


Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks

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 


Learning to Autofocus

Charles Herrmann, Richard Strong Bowen, Neal WadhwaRahul GargQiurui HeJonathan T. BarronRamin 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 LiuShu ZhangAseem 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. BarronRichard TuckerNoah 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 TrullsAndrea 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 LaiAbhijit KunduZhichao LuVivek RathodTom FunkhouserCaroline PantofaruDavid 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 OdenaHan Zhang, Alex Dimakis


Fast Sparse ConvNets

Erich Elsen, Marat DukhanTrevor 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 LaiMing-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


Embodied AI

Organizers include: Alexander ToshevJie TanAleksandra FaustAnelia Angelova


The 1st International Workshop and Prize Challenge on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture

Organizers include: Zhen LiJim Yuan


New Trends in Image Restoration and Enhancement workshop and challenges on image and video restoration and enhancement (NTIRE)

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 BerentRahul Sukthankar


AI for Content Creation

Organizers include: Deqing Sun, Lu JiangWeilong Yang


Fourth Workshop on Computer Vision for AR/VR

Organizers include: Sofien Bouaziz


Low-Power Computer Vision Competition (LPCVC)

Organizers include: Bo ChenAndrew HowardJaeyoun Kim


Sight and Sound

Organizers include: William Freeman


Workshop on Efficient Deep Learning for Computer Vision

Organizers include: Pete Warden


Extreme classification in computer vision

Organizers include: Ramin ZabihZhen 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 MontesJordi Pont-TusetKevis-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-ChenSerge 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 SunMing-Hsuan Yang


Novel View Synthesis: From Depth-Based Warping to Multi-Plane Images and Beyond

Organizers include:Varun Jampani


How to Write a Good Review

Talks by:Vittorio Ferrari, Bill Freeman, Jordi Pont-Tuset


Neural Rendering

Organizers include:Ricardo Martin-BruallaRohit K. PandeySean Fanello,Maneesh AgrawalaDan 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)
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