Multi-view stereo in the deep learning era: A comprehensive review
Multi-view stereo infers the 3D geometry from a set of images captured from several known
positions and viewpoints. It is one of the most important components of 3D reconstruction …
positions and viewpoints. It is one of the most important components of 3D reconstruction …
Neuralangelo: High-fidelity neural surface reconstruction
Neural surface reconstruction has been shown to be powerful for recovering dense 3D
surfaces via image-based neural rendering. However, current methods struggle to recover …
surfaces via image-based neural rendering. However, current methods struggle to recover …
Iterative geometry encoding volume for stereo matching
Abstract Recurrent All-Pairs Field Transforms (RAFT) has shown great potentials in
matching tasks. However, all-pairs correlations lack non-local geometry knowledge and …
matching tasks. However, all-pairs correlations lack non-local geometry knowledge and …
Unifying voxel-based representation with transformer for 3d object detection
In this work, we present a unified framework for multi-modality 3D object detection, named
UVTR. The proposed method aims to unify multi-modality representations in the voxel space …
UVTR. The proposed method aims to unify multi-modality representations in the voxel space …
A tutorial review on point cloud registrations: principle, classification, comparison, and technology challenges
A point cloud as a collection of points is poised to bring about a revolution in acquiring and
generating three‐dimensional (3D) surface information of an object in 3D reconstruction …
generating three‐dimensional (3D) surface information of an object in 3D reconstruction …
Bevstereo: Enhancing depth estimation in multi-view 3d object detection with temporal stereo
Restricted by the ability of depth perception, all Multi-view 3D object detection methods fall
into the bottleneck of depth accuracy. By constructing temporal stereo, depth estimation is …
into the bottleneck of depth accuracy. By constructing temporal stereo, depth estimation is …
Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
We present MVSNeRF, a novel neural rendering approach that can efficiently reconstruct
neural radiance fields for view synthesis. Unlike prior works on neural radiance fields that …
neural radiance fields for view synthesis. Unlike prior works on neural radiance fields that …
Patchmatchnet: Learned multi-view patchmatch stereo
We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for
high-resolution multi-view stereo. With high computation speed and low memory …
high-resolution multi-view stereo. With high computation speed and low memory …
Cascade cost volume for high-resolution multi-view stereo and stereo matching
The deep multi-view stereo (MVS) and stereo matching approaches generally construct 3D
cost volumes to regularize and regress the output depth or disparity. These methods are …
cost volumes to regularize and regress the output depth or disparity. These methods are …
Rethinking depth estimation for multi-view stereo: A unified representation
Depth estimation is solved as a regression or classification problem in existing learning-
based multi-view stereo methods. Although these two representations have recently …
based multi-view stereo methods. Although these two representations have recently …