S23DR 2026 Winning Solution
Quick Answer
This paper shows that The S23DR 2026 challenge's winning solution utilizes a flow-matching DiT for structured 3D wireframe reconstruction, achieving an HSS of 0.654.
Quick Take
The S23DR 2026 challenge's winning solution utilizes a flow-matching DiT for structured 3D wireframe reconstruction, achieving an HSS of 0.654. The method employs a two-pass approach for refinement and maintains performance through a multi-sample consensus step, ranking first on the private leaderboard.
Key Points
- Winning solution for S23DR 2026 challenge focused on 3D wireframe reconstruction.
- Utilizes flow-matching DiT conditioned on Perceiver-style scene tokens.
- Achieved a high score of HSS = 0.654 on the private leaderboard.
- Incorporates a two-pass approach for structure refinement.
- Employs a multi-sample consensus step to enhance stochastic sampling.
Article Excerpt
From source RSS / original summaryarXiv:2606. 06695v1 Announce Type: new Abstract: This text presents the winning solution to the S23DR 2026 challenge for structured 3D wireframe reconstruction from sparse SfM, fitted depth, and semantic segmentations. The method treats vertices as a conditional set and denoises 64 vertex tokens with a flow-matching DiT conditioned on Perceiver-style scene tokens.
A global pass predicts the coarse structure, a hull-cropped second pass refines it, and a small multi-sample consensus step keeps the stochastic sampler well behaved. The final system ranked first on the private leaderboard, achievingHSS = 0. 654.
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