Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields-Reference-Cited by-同舟云学术

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Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Agaram Rohith¹,Dewan Shaurya¹,Sajnani Rahul²,Poulenard Adrien³,Krishna Madhava¹,Sridhar Srinath²

Affiliation:

1. IIIT-Hyderabad,RRC

2. Brown University

3. Stanford University

Funder

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10205012.pdf?arnumber=10205012

Reference69 articles.

1. Learning Steerable Filters for Rotation Equivariant CNNs

2. A Papier-Mache Approach to Learning 3D Surface Generation

3. 3d steerable cnns: Learning rotationally equivariant features in volumetric data;weiler;NIPS,2018

4. Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SOCS: Semantically-aware Object Coordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variations;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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