Papers › MonoScene: Monocular 3D Semantic Scene Completion
MonoScene: Monocular 3D Semantic Scene Completion
Anh-Quan Cao, Raoul de Charette
MonoScene proposes a 3D Semantic Scene Completion (SSC) framework, where the dense geometry and semantics of a scene are inferred from a single monocular RGB image. Different from the SSC literature, relying on 2.5 or 3D input, we solve the complex problem of 2D to 3D scene reconstruction while jointly inferring its semantics. Our framework relies on successive 2D and 3D UNets bridged by a novel 2D-3D features projection inspiring from optics and introduces a 3D context relation prior to enforce spatio-semantic consistency. Along with architectural contributions, we introduce novel global scene and local frustums losses. Experiments show we outperform the literature on all metrics and datasets while hallucinating plausible scenery even beyond the camera field of view. Our code and trained models are available at https://github.com/cv-rits/MonoScene.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Semantic Scene Completion | KITTI-360 | MonoScene | mIoU | 12.31 | #6 of 7 | Archive leaderboard | report |
| 3D Semantic Scene Completion | NYUv2 | MonoScene (RGB input only) | mIoU | 26.94 | #25 of 28 | Archive leaderboard | report |
| 3D Semantic Scene Completion | SemanticKITTI | MonoScene (RGB input only) | mIoU | 11.08 | #18 of 20 | Archive leaderboard | report |
| 3D Semantic Scene Completion from a single RGB image | KITTI-360 | MonoScene | mIoU | 12.31 | #3 of 4 | Archive leaderboard | report |
| 3D Semantic Scene Completion from a single RGB image | NYUv2 | MonoScene | mIoU | 26.94 | #3 of 6 | Archive leaderboard | report |
| 3D Semantic Scene Completion from a single RGB image | SemanticKITTI | MonoScene | mIoU | 11.08 | #6 of 9 | 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.
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