A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation-Reference-Cited by-同舟云学术

A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Mu Jiteng¹,Qiu Weichao²,Kortylewski Adam²,Yuille Alan²,Vasconcelos Nuno¹,Wang Xiaolong¹

Affiliation:

1. UC San Diego

2. Johns Hopkins University

Publisher

IEEE

Link

Reference92 articles.

1. Test-time training with self-supervision for generalization under distribution shifts;sun;ICML,2020

2. Scene representation networks: Continuous 3d-structure-aware neural scene representations;sitzmann;NeurIPS 2019,2019

3. Implicit neural representations with periodic activation functions;sitzmann;CoRR,2020

5. GRF: learning a general radiance field for 3d scene representation and rendering;trevithick;CoRR,2020

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