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SOTA
三维重建
3D Reconstruction On Dtu
3D Reconstruction On Dtu
评估指标
Acc
Comp
Overall
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Acc
Comp
Overall
Paper Title
Repository
PatchmatchNet
0.427
0.277
0.352
PatchmatchNet: Learned Multi-View Patchmatch Stereo
EPP-MVSNet
0.413
0.296
0.355
EPP-MVSNet: Epipolar-Assembling Based Depth Prediction for Multi-View Stereo
-
COLMAP
0.400
0.664
0.532
Structure-From-Motion Revisited
-
3D-R2N2
0.397
0.884
0.630
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
MVSNet
0.396
0.527
0.462
MVSNet: Depth Inference for Unstructured Multi-view Stereo
MSCVP-MVSNet
0.379
0.278
0.328
Cost Volume Pyramid Network with Multi-strategies Range Searching for Multi-view Stereo
AA-RMVSNet
0.376
0.339
0.357
AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network
Vis-MVSNet
0.369
0.361
0.365
Visibility-aware Multi-view Stereo Network
UniMVSNet
0.352
0.278
0.315
Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation
CDS-MVSNet
0.351
0.278
0.315
Curvature-guided dynamic scale networks for Multi-view Stereo
GoMVS
0.347
0.227
0.287
GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo
UCSNet
0.338
0.349
0.344
Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness
IB-MVS
0.334
0.309
0.321
IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions
-
GeoMVSNet
0.331
0.259
0.295
GeoMVSNet: Learning Multi-View Stereo With Geometry Perception
-
GC-MVSNet
0.330
0.260
0.295
GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo
ET-MVSNet
0.329
0.253
0.291
When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo
MVSFormer
0.327
0.251
0.289
MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth
RA-MVSNet
0.326
0.268
0.297
Multi-View Stereo Representation Revisit: Region-Aware MVSNet
-
Cas-MVSNet
0.325
0.385
0.355
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching
TransMVSNet
0.321
0.289
0.305
TransMVSNet: Global Context-aware Multi-view Stereo Network with Transformers
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