Google at CVPR 2021

Posted by Emily Knapp and Tim Herrmann, Program Managers

This week marks the start of the 2021 Conference on Computer Vision and Pattern Recognition (CVPR 2021), the premier annual computer vision event consisting of the main conference, workshops and tutorials. As a leader in computer vision research and a Champion Level Sponsor, Google will have a strong presence at CVPR 2021, with over 70 publications accepted, along with the organization of and participation in multiple workshops and tutorials.

If you are participating in CVPR this year, please visit our virtual booth to learn about Google research into the next generation of intelligent systems that utilize the latest machine learning techniques applied to various areas of machine perception.

You can also learn more about our research being presented at CVPR 2021 in the list below (Google affiliations in bold).

Organizing Committee Members

General Chair: Rahul Sukthankar
Finance Chair: Ramin Zabih
Workshop Chair: Caroline Pantofaru
Area Chairs: Chen Sun, Golnaz Ghiasi, Jonathan Barron, Kostas Rematas, Negar Rostamzadeh, Noah Snavely, Sanmi Koyejo, Tsung-Yi Lin


Cross-Modal Contrastive Learning for Text-to-Image Generation (see the blog post)
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee*, Yinfei Yang

Learning Graph Embeddings for Compositional Zero-Shot Learning
Muhammad Ferjad Naeem, Yongqin Xian, Federico Tombari, Zeynep Akata

SPSG: Self-Supervised Photometric Scene Generation From RGB-D Scans
Angela Dai, Yawar Siddiqui, Justus Thies, Julien Valentin, Matthias Nießner

3D-MAN: 3D Multi-Frame Attention Network for Object Detection
Zetong Yang*, Yin Zhou, Zhifeng Chen, Jiquan Ngiam

MIST: Multiple Instance Spatial Transformer
Baptiste Angles, Yuhe Jin, Simon Kornblith, Andrea Tagliasacchi, Kwang Moo Yi

OCONet: Image Extrapolation by Object Completion
Richard Strong Bowen*, Huiwen Chang, Charles Herrmann*, Piotr Teterwak*, Ce Liu, Ramin Zabih

Ranking Neural Checkpoints
Yandong Li, Xuhui Jia, Ruoxin Sang, Yukun Zhu, Bradley Green, Liqiang Wang, Boqing Gong

LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces

This article is purposely trimmed, please visit the source to read the full article.

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