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

2 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2024

Query Quantized Neural SLAM

Sijia Jiang, Jing Hua, Zhizhong Han

Neural implicit representations have shown remarkable abilities in jointly modeling geometry, color, and camera poses in simultaneous localization and mapping (SLAM). Current metho…

cs.CV2024

Sensing Surface Patches in Volume Rendering for Inferring Signed Distance Functions

Sijia Jiang, Tong Wu, Jing Hua +1

It is vital to recover 3D geometry from multi-view RGB images in many 3D computer vision tasks. The latest methods infer the geometry represented as a signed distance field by mini…

cs.CV2024

Fast Learning of Signed Distance Functions from Noisy Point Clouds via Noise to Noise Mapping

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

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

cs.CV20231 cited

GridPull: Towards Scalability in Learning Implicit Representations from 3D Point Clouds

Chao Chen, Yu-Shen Liu, Zhizhong Han

Learning implicit representations has been a widely used solution for surface reconstruction from 3D point clouds. The latest methods infer a distance or occupancy field by overfit…

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.CV20231 cited

Coordinate Quantized Neural Implicit Representations for Multi-view Reconstruction

Sijia Jiang, Jing Hua, Zhizhong Han

In recent years, huge progress has been made on learning neural implicit representations from multi-view images for 3D reconstruction. As an additional input complementing coordina…