4 citations · 9 across the 5 of their papers we have counts for
5 papers
High-fidelity 3D Gaussian Inpainting: preserving multi-view consistency and photorealistic details
Jun Zhou, Dinghao Li, Nannan Li +1
Recent advancements in multi-view 3D reconstruction and novel-view synthesis, particularly through Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have greatly enha…
Refining 3D Point Cloud Normal Estimation via Sample Selection
Jun Zhou, Yaoshun Li, Hongchen Tan +3
In recent years, point cloud normal estimation, as a classical and foundational algorithm, has garnered extensive attention in the field of 3D geometric processing. Despite the rem…
Local Aggressive Adversarial Attacks on 3D Point Cloud
Yiming Sun, Feng Chen, Zhiyu Chen +1
Deep neural networks are found to be prone to adversarial examples which could deliberately fool the model to make mistakes. Recently, a few of works expand this task from 2D image…
Improvement of Normal Estimation for PointClouds via Simplifying Surface Fitting
Jun Zhou, Wei Jin, Mingjie Wang +3
With the burst development of neural networks in recent years, the task of normal estimation has once again become a concern. By introducing the neural networks to classic methods…
Fast and Accurate Normal Estimation for Point Cloud via Patch Stitching
Jun Zhou, Wei Jin, Mingjie Wang +3
This paper presents an effective normal estimation method adopting multi-patch stitching for an unstructured point cloud. The majority of learning-based approaches encode a local p…