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cs.CV2022
An Efficient End-to-End 3D Voxel Reconstruction based on Neural Architecture Search
Yongdong Huang, Yuanzhan Li, Xulong Cao +5
Using neural networks to represent 3D objects has become popular. However, many previous works employ neural networks with fixed architecture and size to represent different 3D obj…
cs.CV2022
High-fidelity 3D Model Compression based on Key Spheres
Yuanzhan Li, Yuqi Liu, Yujie Lu +3
In recent years, neural signed distance function (SDF) has become one of the most effective representation methods for 3D models. By learning continuous SDFs in 3D space, neural ne…
cs.CV2021
SN-Graph: a Minimalist 3D Object Representation for Classification
Siyu Zhang, Hui Cao, Yuqi Liu +4
Using deep learning techniques to process 3D objects has achieved many successes. However, few methods focus on the representation of 3D objects, which could be more effective for…