Search Results for author:
Found 4 papers, 3 papers with code
AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network
To overcome the difficulty of varying occlusion in complex scenes, we propose an inter-view cost volume aggregation module for adaptive pixel-wise view aggregation, which is able to preserve better-matched pairs among all views.
Ranked #10 on
Point Clouds
on Tanks and Temples
(Mean F1 (Intermediate) metric)
Deep Learning for Multi-View Stereo via Plane Sweep: A Survey
3D reconstruction has lately attracted increasing attention due to its wide application in many areas, such as autonomous driving, robotics and virtual reality.
Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking
In this paper, we propose an efficient and effective dense hybrid recurrent multi-view stereo net with dynamic consistency checking, namely $D^{2}$HC-RMVSNet, for accurate dense point cloud reconstruction.
Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
n this paper, we propose an effective and efficient pyramid multi-view stereo (MVS) net with self-adaptive view aggregation for accurate and complete dense point cloud reconstruction.
