Results for ADS-MVSNet
Submission data
Full name | An attention-based and deep sparse priori cascade multi-view stereo network |
Description | In this study, we aim to improve feature matching correlation, aggregate global contextual information, and enhance the robustness of depth estimation to improve the quality of the reconstruction.
We propose an attention-based deep sparse priori cascade multi-view stereo network, ADS-MVSNet. Firstly, we propose a feature extraction module based on the attention mechanism to obtain the regions of interest in the input scene. Secondly, we propose a depth sparse prior strategy module to estimate the depth map of the input scene more accurately. It is followed by refinement of the initial depth map using a coarse-to-fine method to improve the accuracy of point cloud reconstruction. |
Programming language(s) | python |
Hardware | Intel Xeon CPU E5-2697, 32GB RAM, NVIDIA GTX 1080 8GB |
Submission creation date | 22 May, 2023 |
Last edited | 23 Jun, 2023 |
High-res multi-view results
Info | all | high-res multi-view | indoor | outdoor | botani. | boulde. | bridge | door | exhibi. | lectur. | living. | lounge | observ. | old co. | statue | terrac. |
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61.90 | 62.19 | 61.03 | 73.16 | 36.42 | 67.10 | 61.75 | 49.74 | 66.04 | 82.97 | 46.71 | 63.21 | 42.29 | 69.96 | 83.46 |
Low-res many-view results
Info | all | low-res many-view | indoor | outdoor | lakeside | sand box | storage room | storage room 2 | tunnel |
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No results yet. |
Low-res two-view results
SLAM results
all | boxes | boxes dark | buddha | cables 4 | cables 5 | desk 1 | desk 2 | desk changing 2 | desk dark 1 | desk dark 2 | desk global light changes | desk ir light | dino | drone | foreground occlusion | helmet | kidnap 2 | lamp | large loop 2 | large loop 3 | large non loop | motion 2 | motion 3 | motion 4 | planar 1 | reflective 2 | scale change | table 1 | table 2 | table 5 | table 6 | table global light changes | table local light changes | table scene | trashbin | |||
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Method | Info | |||||||||||||||||||||||||||||||||||||
No results yet. |