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Research map / Detection and segmentation / 3D detection and driving

AShapeFormer: Semantics-Guided Object-Level Active Shape Encoding for 3D Object Detection via Transformers

CVPR 2023 · Detection and segmentation › 3D detection and driving · approach: Unified LiDAR 3D detection · 19 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add AShapeFormer to VoteNetVoteNet · SUN RGB-D validationmAP@0.25: 57.7 -> 61.2Helped
Add AShapeFormer to imVoteNetimVoteNet · SUN RGB-D validationmAP@0.25: 63.4 -> 65.1Helped
Add AShapeFormer to VoteNetVoteNet · ScanNet V2 validationmAP@0.5: 33.5 -> 41.6Helped
Add AShapeFormer to GroupFree3DGroupFree3D · ScanNet V2 validationmAP@0.25: 69.1 -> 70.4Helped
Add naive shape encoding (ablation)VoteNet · SUN RGB-DmAP@0.25: 57.7 -> 58.9Helped
Add SGM to naive shape encoding (ablation)VoteNet with naive shape encoding · SUN RGB-DmAP@0.25: 58.9 -> 59.5Helped
Use ShapeFormer instead of naive shape encoding, without SGM (ablation)VoteNet · SUN RGB-DmAP@0.25: 58.9 -> 59.9Helped
Add SGM to ShapeFormer (ablation)VoteNet with ShapeFormer · SUN RGB-DmAP@0.25: 59.9 -> 61.2Helped

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