most citedUni3D: Exploring Unified 3D Representation at Scale

9 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2024

UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion

Junsheng Zhou, Weiqi Zhang, Baorui Ma +3

Diffusion models have shown remarkable results for image generation, editing and inpainting. Recent works explore diffusion models for 3D shape generation with neural implicit func…

cs.CV20239 cited

Uni3D: Exploring Unified 3D Representation at Scale

Junsheng Zhou, Jinsheng Wang, Baorui Ma +3

Scaling up representations for images or text has been extensively investigated in the past few years and has led to revolutions in learning vision and language. However, scalable…

cs.CV20231 cited

Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection

Junsheng Zhou, Baorui Ma, Shujuan Li +2

Latest methods represent shapes with open surfaces using unsigned distance functions (UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the gradients ar…

cs.CV20233 cited

Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping

Baorui Ma, Yu-Shen Liu, Zhizhong Han

Learning signed distance functions (SDFs) from 3D point clouds is an important task in 3D computer vision. However, without ground truth signed distances, point normals or clean po…

cs.CV20232 cited

Towards Better Gradient Consistency for Neural Signed Distance Functions via Level Set Alignment

Baorui Ma, Junsheng Zhou, Yu-Shen Liu +1

Neural signed distance functions (SDFs) have shown remarkable capability in representing geometry with details. However, without signed distance supervision, it is still a challeng…