Papers › Semantic Scene Completion from a Single Depth Image
Semantic Scene Completion from a Single Depth Image
Shuran Song, Fisher Yu, Andy Zeng, Angel X. Chang, Manolis Savva, Thomas Funkhouser
This paper focuses on semantic scene completion, a task for producing a complete 3D voxel representation of volumetric occupancy and semantic labels for a scene from a single-view depth map observation. Previous work has considered scene completion and semantic labeling of depth maps separately. However, we observe that these two problems are tightly intertwined. To leverage the coupled nature of these two tasks, we introduce the semantic scene completion network (SSCNet), an end-to-end 3D convolutional network that takes a single depth image as input and simultaneously outputs occupancy and semantic labels for all voxels in the camera view frustum. Our network uses a dilation-based 3D context module to efficiently expand the receptive field and enable 3D context learning. To train our network, we construct SUNCG - a manually created large-scale dataset of synthetic 3D scenes with dense volumetric annotations. Our experiments demonstrate that the joint model outperforms methods addressing each task in isolation and outperforms alternative approaches on the semantic scene completion task.
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Semantic Scene Completion | KITTI-360 | SSCNet | mIoU | 16.95 | #2 of 7 | Archive leaderboard | report |
| 3D Semantic Scene Completion | NYUv2 | SSCNet (SUNCG pretraining) | mIoU | 30.5 | #19 of 28 | Archive leaderboard | report |
| 3D Semantic Scene Completion | NYUv2 | SSCNet | mIoU | 24.7 | #27 of 28 | Archive leaderboard | report |
| 3D Semantic Scene Completion | SemanticKITTI | SSCNet (reported in LMSCNet) | mIoU | 16.1 | #13 of 20 | Archive leaderboard | report |
| 3D Semantic Scene Completion | SemanticKITTI | SSCNet-full (reported in LMSCNet) | mIoU | 16.1 | #14 of 20 | 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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