70 citations · 205 across the 31 of their papers we have counts for
10 papers · 1 filter
Laplacian Frequency Hierarchies for Efficient 3D Gaussian Splatting Training
Yixiong Yang, Sisheng Zhang, Qingsong Yan +2
A key bottleneck in 3D Gaussian Splatting training is the continual growth of Gaussian primitives, which increases optimization cost and slows convergence, especially at high resol…
RA-NeRF: Robust Neural Radiance Field Reconstruction with Accurate Camera Pose Estimation under Complex Trajectories
Qingsong Yan, Qiang Wang, Kaiyong Zhao +4
Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have emerged as powerful tools for 3D reconstruction and SLAM tasks. However, their performance depends heavily on ac…
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion
Qingsong Yan, Qiang Wang, Kaiyong Zhao +4
Due to the rapid development of panorama cameras, the task of estimating panorama depth has attracted significant attention from the computer vision community, especially in applic…
ParZC: Parametric Zero-Cost Proxies for Efficient NAS
Peijie Dong, Lujun Li, Xinglin Pan +4
Recent advancements in Zero-shot Neural Architecture Search (NAS) highlight the efficacy of zero-cost proxies in various NAS benchmarks. Several studies propose the automated desig…
CF-NeRF: Camera Parameter Free Neural Radiance Fields with Incremental Learning
Qingsong Yan, Qiang Wang, Kaiyong Zhao +4
Neural Radiance Fields (NeRF) have demonstrated impressive performance in novel view synthesis. However, NeRF and most of its variants still rely on traditional complex pipelines t…
Rethinking Disparity: A Depth Range Free Multi-View Stereo Based on Disparity
Qingsong Yan, Qiang Wang, Kaiyong Zhao +3
Existing learning-based multi-view stereo (MVS) methods rely on the depth range to build the 3D cost volume and may fail when the range is too large or unreliable. To address this…
EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching
Qiang Wang, Shaohuai Shi, Kaiyong Zhao +1
Recent advanced studies have spent considerable human efforts on optimizing network architectures for stereo matching but hardly achieved both high accuracy and fast inference spee…
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
Qiang Wang, Shaohuai Shi, Shizhen Zheng +2
Deep neural networks (DNNs) have achieved great success in the area of computer vision. The disparity estimation problem tends to be addressed by DNNs which achieve much better pre…
FADNet: A Fast and Accurate Network for Disparity Estimation
Qiang Wang, Shaohuai Shi, Shizhen Zheng +2
Deep neural networks (DNNs) have achieved great success in the area of computer vision. The disparity estimation problem tends to be addressed by DNNs which achieve much better pre…
IRS: A Large Naturalistic Indoor Robotics Stereo Dataset to Train Deep Models for Disparity and Surface Normal Estimation
Qiang Wang, Shizhen Zheng, Qingsong Yan +3
Indoor robotics localization, navigation, and interaction heavily rely on scene understanding and reconstruction. Compared to the monocular vision which usually does not explicitly…