Papers › Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization
Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang
The reconstruction of low-textured areas is a prominent research focus in multi-view stereo (MVS). In recent years, traditional MVS methods have performed exceptionally well in reconstructing low-textured areas by constructing plane models. However, these methods often encounter issues such as crossing object boundaries and limited perception ranges, which undermine the robustness of plane model construction. Building on previous work (APD-MVS), we propose the DPE-MVS method. By introducing dual-level precision edge information, including fine and coarse edges, we enhance the robustness of plane model construction, thereby improving reconstruction accuracy in low-textured areas. Furthermore, by leveraging edge information, we refine the sampling strategy in conventional PatchMatch MVS and propose an adaptive patch size adjustment approach to optimize matching cost calculation in both stochastic and low-textured areas. This additional use of edge information allows for more precise and robust matching. Our method achieves state-of-the-art performance on the ETH3D and Tanks & Temples benchmarks. Notably, our method outperforms all published methods on the ETH3D benchmark.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multi-View 3D Reconstruction | ETH3D | DPE-MVS | F1 score | 89.48 | #1 of 5 | Archive leaderboard | report |
| Point Clouds | Tanks and Temples | DPE-MVS | Mean F1 (Advanced) | 40.20 | #5 of 21 | Archive leaderboard | report |
| Point Clouds | Tanks and Temples | DPE-MVS | Mean F1 (Intermediate) | 63.98 | #5 of 21 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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