Research map / Detection and segmentation / 3D detection and driving
AShapeFormer: Semantics-Guided Object-Level Active Shape Encoding for 3D Object Detection via Transformers
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add AShapeFormer to VoteNet | VoteNet · SUN RGB-D validation | mAP@0.25: 57.7 -> 61.2 | Helped |
| Add AShapeFormer to imVoteNet | imVoteNet · SUN RGB-D validation | mAP@0.25: 63.4 -> 65.1 | Helped |
| Add AShapeFormer to VoteNet | VoteNet · ScanNet V2 validation | mAP@0.5: 33.5 -> 41.6 | Helped |
| Add AShapeFormer to GroupFree3D | GroupFree3D · ScanNet V2 validation | mAP@0.25: 69.1 -> 70.4 | Helped |
| Add naive shape encoding (ablation) | VoteNet · SUN RGB-D | mAP@0.25: 57.7 -> 58.9 | Helped |
| Add SGM to naive shape encoding (ablation) | VoteNet with naive shape encoding · SUN RGB-D | mAP@0.25: 58.9 -> 59.5 | Helped |
| Use ShapeFormer instead of naive shape encoding, without SGM (ablation) | VoteNet · SUN RGB-D | mAP@0.25: 58.9 -> 59.9 | Helped |
| Add SGM to ShapeFormer (ablation) | VoteNet with ShapeFormer · SUN RGB-D | mAP@0.25: 59.9 -> 61.2 | Helped |
Closest papers by meaning
- Straight to Shapes: Real-Time Detection of Encoded Shapes (CVPR 2017 · similarity 0.89)
- SEFormer: Structure Embedding Transformer for 3D Object Detection (AAAI 2023 · similarity 0.87)
- Point2Seq: Detecting 3D Objects As Sequences (CVPR 2022 · similarity 0.87)
- DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes (CVPR 2020 · similarity 0.87)
- Cubify Anything: Scaling Indoor 3D Object Detection (CVPR 2025 · similarity 0.86)
- ImOV3D: Learning Open Vocabulary Point Clouds 3D Object Detection from Only 2D Images (NeurIPS 2024 · similarity 0.86)
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