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20222026
most citedCAP-UDF: Learning Unsigned Distance Functions Progressively from Raw Point Clouds with Consistency-Aware Field Optimization

28 citations · 30 across the 8 of their papers we have counts for

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cs.CV2026

TARS: Timestep-Aware Data Scaling for 3D-Free Video Re-Shooting

Jiwen Liu, Shujuan Li, Xiaohan Li +5

Video re-shooting aims to regenerate videos with controllable camera motion and viewpoint. Existing methods rely on explicit 3D priors, which are limited by reconstruction quality…

cs.CV2026

Vera: Identity-Faithful Human Subject-to-Video Generation

Yulong Xu, Xinyue Liu, Shujuan Li +6

Subject-to-video (S2V) generation has made substantial progress in preserving reference subjects across diverse categories, yet generic subject consistency remains insufficient for…

cs.CV2026

OmniDirector: General Multi-Shot Camera Cloning without Cross-Paired Data

Jiwen Liu, Shujuan Li, Zhixue Fang +8

Cloning camera motion from reference videos is an important task in video generation, as videos provide intuitive and precise control. Existing methods either directly use parametr…

cs.CV2025

GaussianUDF: Inferring Unsigned Distance Functions through 3D Gaussian Splatting

Shujuan Li, Yu-Shen Liu, Zhizhong Han

Reconstructing open surfaces from multi-view images is vital in digitalizing complex objects in daily life. A widely used strategy is to learn unsigned distance functions (UDFs) by…

cs.CV2023

Learning Continuous Implicit Field with Local Distance Indicator for Arbitrary-Scale Point Cloud Upsampling

Shujuan Li, Junsheng Zhou, Baorui Ma +2

Point cloud upsampling aims to generate dense and uniformly distributed point sets from a sparse point cloud, which plays a critical role in 3D computer vision. Previous methods ty…

cs.CV2023★ 1 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.CV2022★ 1 cited

NeAF: Learning Neural Angle Fields for Point Normal Estimation

Shujuan Li, Junsheng Zhou, Baorui Ma +2

Normal estimation for unstructured point clouds is an important task in 3D computer vision. Current methods achieve encouraging results by mapping local patches to normal vectors o…

cs.CV2022★ 28 cited

CAP-UDF: Learning Unsigned Distance Functions Progressively from Raw Point Clouds with Consistency-Aware Field Optimization

Junsheng Zhou, Baorui Ma, Shujuan Li +3

Surface reconstruction for point clouds is an important task in 3D computer vision. Most of the latest methods resolve this problem by learning signed distance functions from point…