1 citations · 3 across the 5 of their papers we have counts for
6 papers · 1 filter
LookCloser: Frequency-aware Radiance Field for Tiny-Detail Scene
Xiaoyu Zhang, Weihong Pan, Chong Bao +4
Humans perceive and comprehend their surroundings through information spanning multiple frequencies. In immersive scenes, people naturally scan their environment to grasp its overa…
GeoTexDensifier: Geometry-Texture-Aware Densification for High-Quality Photorealistic 3D Gaussian Splatting
Hanqing Jiang, Xiaojun Xiang, Han Sun +4
3D Gaussian Splatting (3DGS) has recently attracted wide attentions in various areas such as 3D navigation, Virtual Reality (VR) and 3D simulation, due to its photorealistic and ef…
Quadratic Gaussian Splatting: High Quality Surface Reconstruction with Second-order Geometric Primitives
Ziyu Zhang, Binbin Huang, Hanqing Jiang +3
We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intri…
LiVisSfM: Accurate and Robust Structure-from-Motion with LiDAR and Visual Cues
Hanqing Jiang, Liyang Zhou, Zhuang Zhang +2
This paper presents an accurate and robust Structure-from-Motion (SfM) pipeline named LiVisSfM, which is an SfM-based reconstruction system that fully combines LiDAR and visual cue…
Depth-NeuS: Neural Implicit Surfaces Learning for Multi-view Reconstruction Based on Depth Information Optimization
Hanqi Jiang, Cheng Zeng, Runnan Chen +4
Recently, methods for neural surface representation and rendering, for example NeuS, have shown that learning neural implicit surfaces through volume rendering is becoming increasi…
Deep Fundamental Matrix Estimation without Correspondences
Omid Poursaeed, Guandao Yang, Aditya Prakash +4
Estimating fundamental matrices is a classic problem in computer vision. Traditional methods rely heavily on the correctness of estimated key-point correspondences, which can be no…