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PatchmatchNet: Learned Multi-View Patchmatch Stereo
[article]
2020
arXiv
pre-print
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We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. ...
For the first time we introduce an iterative multi-scale Patchmatch in an end-to-end trainable architecture and improve the Patchmatch core algorithm with a novel and learned adaptive propagation and evaluation ...
In this work, we propose PatchmatchNet, a novel cascade formulation of learning-based Patchmatch, which aims at decreasing memory consumption and run-time for highresolution multi-view stereo. ...
arXiv:2012.01411v1
fatcat:kzbuchbjw5hkvmd5slzpwvqt4a
DDL-MVS: Depth Discontinuity Learning for MVS Networks
[article]
2022
arXiv
pre-print
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Traditional MVS methods have good accuracy but struggle with completeness, while recently developed learning-based multi-view stereo (MVS) techniques have improved completeness except accuracy being compromised ...
We propose depth discontinuity learning for MVS methods, which further improves accuracy while retaining the completeness of the reconstruction. ...
Using this depth representation, we improve multi-view depth reconstruction, especially across geometric boundaries.
introduced a learning-based Multi-View PatchMatch Stereo pipeline. ...
arXiv:2203.01391v2
fatcat:wkuqjxurdzdk3ajb4qyzhfzmeq
IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo
[article]
2021
arXiv
pre-print
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We present IterMVS, a new data-driven method for high-resolution multi-view stereo. ...
Ingesting multi-scale matching information, our model refines these distributions over multiple iterations and infers depth and confidence. ...
Patchmatchnet: Learned
multi-view patchmatch stereo. ...
arXiv:2112.05126v1
fatcat:hwlfy6g5xvbzbkww5e2zihxthm
DENSE RECONSTRUCTION FOR TUNNELS BASED ON THE INTEGRATION OF DOUBLE-LINE PARALLEL PHOTOGRAPHY AND DEEP LEARNING
2022
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Stereo techniques. ...
surfaces make occlusion unavoidable, and the pixel scales vary evidently in parallel photography, both of which make it difficult to obtain expected models neither by Semi-Global Matching nor by Patch-based Multi-view ...
The training strategy of PatchmatchNet adopted in this paper is based on Pixelwise Visibility-aware multi-view Stereo Network (PVSNet). ...
doi:10.5194/isprs-archives-xliii-b2-2022-1117-2022
fatcat:bsm3lwstarbkthqiq3fvudzmu4
PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility
[article]
2021
arXiv
pre-print
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Recent learning-based multi-view stereo (MVS) methods show excellent performance with dense cameras and small depth ranges. ...
However, non-learning based approaches still outperform for scenes with large depth ranges and sparser wide-baseline views, in part due to their PatchMatch optimization over pixelwise estimates of depth ...
PatchMatch-RL MVS We propose PatchMatch-RL, an end-to-end learning framework that uses PatchMatch for Multi-View Stereo (MVS) reconstruction. Figure 2 shows an overview of our approach. ...
arXiv:2108.08943v1
fatcat:47vla23zoveifdaywzdokaxsoe
MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions
[article]
2021
arXiv
pre-print
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Deep learning has made significant impacts on multi-view stereo systems. ...
We present , a highly efficient multi-view stereo algorithm that seamlessly integrates multi-view constraints into single-view networks via an attention mechanism. ...
Related Works Recent advances of multi-view stereo. ...
arXiv:2104.13325v2
fatcat:zplvazdtevefhlf5ban2cwizda
Non-parametric Depth Distribution Modelling based Depth Inference for Multi-view Stereo
[article]
2022
arXiv
pre-print
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Recent cost volume pyramid based deep neural networks have unlocked the potential of efficiently leveraging high-resolution images for depth inference from multi-view stereo. ...
In contrast, we propose constructing the cost volume by non-parametric depth distribution modeling to handle pixels with unimodal and multi-modal distributions. ...
Introduction Multi-view stereo (MVS) aims to infer the 3D structure, represented by a depth map, of a scene from a set of images captured by a camera from multiple viewpoints. ...
arXiv:2205.03783v1
fatcat:siyzfen2zjdhflllwwcnf743pa
Accurate Human Body Reconstruction for Volumetric Video
[article]
2022
arXiv
pre-print
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2021
2021 International Conference on 3D Immersion (IC3D)
unpublished
doi:10.1109/ic3d53758.2021.9687256 fatcat:s4jbmqdc3jbhdf26xfbsyvqihq
doi:10.1109/ic3d53758.2021.9687256 fatcat:s4jbmqdc3jbhdf26xfbsyvqihq
While current volumetric video approaches estimate depth maps using traditional stereo matching techniques, we introduce and optimize deep learning-based multi-view stereo networks for depth map estimation ...
as camera viewing frustums. ...
Multi-view Stereo. ...
arXiv:2202.13118v1
fatcat:nz53fexmkfbifejr3f6fj2ke2e
Generalized Binary Search Network for Highly-Efficient Multi-View Stereo
[article]
2021
arXiv
pre-print
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Multi-view Stereo (MVS) with known camera parameters is essentially a 1D search problem within a valid depth range. ...
Recent deep learning-based MVS methods typically densely sample depth hypotheses in the depth range, and then construct prohibitively memory-consuming 3D cost volumes for depth prediction. ...
Patchmatchnet: Learned
fourth Eurographics symposium on Geometry processing, multi-view patchmatch stereo. ...
arXiv:2112.02338v1
fatcat:ijbzdyri25a7jm2tqv6xcgwjoa
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo
[article]
2022
arXiv
pre-print
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Learning-based Multi-View Stereo (MVS) methods warp source images into the reference camera frustum to form 3D volumes, which are fused as a cost volume to be regularized by subsequent networks. ...
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently. ...
Introduction Given multiple 2D RGB observations and camera parameters, Multi-View Stereo (MVS) aims to reconstruct the dense geometry of the scene. ...
arXiv:2204.07346v1
fatcat:e6lenycj3fas3ow4rd47v5px2q
Multiview Stereo with Cascaded Epipolar RAFT
[article]
2022
arXiv
pre-print
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We address multiview stereo (MVS), an important 3D vision task that reconstructs a 3D model such as a dense point cloud from multiple calibrated images. ...
We propose CER-MVS (Cascaded Epipolar RAFT Multiview Stereo), a new approach based on the RAFT (Recurrent All-Pairs Field Transforms) architecture developed for optical flow. ...
Existing learning-based MVS methods either use learning to improve parts of a classical pipeline such as PatchMatch [11, [39] [40] [41] , or develop end-toend architectures [5, 6, 10, 13, 14, 18, 29, ...
arXiv:2205.04502v1
fatcat:dlrxpbstujevblaafg3odlnlnu
RIAV-MVS: Recurrent-Indexing an Asymmetric Volume for Multi-View Stereo
[article]
2022
arXiv
pre-print
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In this paper, we present a learning-based approach for multi-view stereo (MVS), i.e., estimate the depth map of a reference frame using posed multi-view images. ...
Since the cost volume plays a paramount role in encoding the multi-view geometry, we aim to improve its construction both in pixel- and frame- levels. ...
Related Work Depth can be accurately predicted from stereo matching, which can be broadly divided into binocular stereo and multi-view stereo (MVS). ...
arXiv:2205.14320v1
fatcat:d366purlazhd5muocjbhzi3xp4
IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions
[article]
2021
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We present a novel deep-learning-based method for Multi-View Stereo. ...
This sets it apart from most alternative learning-based Multi-View Stereo methods, where the explicit discretization of the depth space requires the processing of large cost volumes. ...
Our work is inspired by the two-view stereo method in [2] . ...
doi:10.48550/arxiv.2111.14420
fatcat:5b7jhb3tqzfotk5cysltx637si