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MonoATT: Online Monocular 3D Object Detection With Adaptive Token Transformer

CVPR 2023 · Detection and segmentation › 3D detection and driving · approach: Monocular 3D object detection · 43 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use MonoATT instead of MonoDETRKITTI test car detection · KITTI test, carAP3D Hard: +2.01Helped
Add a 3-stage DETR with regular tokens (ablation)GUPNet · KITTI val, carAP3D Hard: 13.72 -> 13.95Helped
Replace regular tokens with adaptive clustering by feature distance, random centers, and mean merging (ablation)GUPNet + 3-stage DETR · KITTI val, carAP3D Hard: 13.95 -> 16.23Helped
Add the image-distance constraint to feature-distance grouping (ablation)ATT with feature-distance grouping · KITTI val, carAP3D Hard: 16.23 -> 16.57Helped
Add attention-weighted token feature merging (ablation)Outline-preferred grouping · KITTI val, carAP3D Hard: 16.57 -> 17.76Helped
Add depth-based cluster-center scoring (ablation)Attention-based merging · KITTI val, carAP3D Hard: 17.76 -> 18.15Helped
Add semantic scoring to depth-based cluster-center scoring (ablation)Depth-scored cluster centers · KITTI val, carAP3D Hard: 18.15 -> 18.87Helped
Add multi-stage feature reconstruction (ablation)Depth-and-semantic cluster centers · KITTI val, carAP3D Hard: 18.87 -> 19.60Helped

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