DeepCurrents: Learning Implicit Representations of Shapes with Boundaries-Reference-Cited by-同舟云学术

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DeepCurrents: Learning Implicit Representations of Shapes with Boundaries

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
Short-container-title:

Author:

Palmer David¹,Smirnov Dmitriy¹,Wang Stephanie²,Chern Albert²,Solomon Justin¹

Affiliation:

1. Massachusetts Institute of Technology

2. UC San Diego

Funder

Army Research Office

Air Force Office of Scientific Research

National Science Foundation

Adobe Systems

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09879635.pdf?arnumber=9879635

Reference71 articles.

1. Learning to reconstruct shapes from unseen classes;zhang;Advances in neural information processing systems,0

3. Lifting Vectorial Variational Problems: A Natural Formulation Based on Geometric Measure Theory and Discrete Exterior Calculus

4. Occupancy Networks: Learning 3D Reconstruction in Function Space

5. Can mean-curvature flow be made non-singular?;kazhdan;Computer Graphics Forum,0

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1. Ray Tracing Harmonic Functions;ACM Transactions on Graphics;2024-07-19

2. SENS: Part‐Aware Sketch‐based Implicit Neural Shape Modeling;Computer Graphics Forum;2024-04-23

3. Mixing-Denoising Generalizable Occupancy Networks;2024 International Conference on 3D Vision (3DV);2024-03-18

4. Sparse Stress Structures from Optimal Geometric Measures;SIGGRAPH Asia 2023 Conference Papers;2023-12-10

5. Robust Zero Level-Set Extraction from Unsigned Distance Fields Based on Double Covering;ACM Transactions on Graphics;2023-12-05

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