XWOD is a large-scale real-world benchmark for traffic object detection under seven extreme weather conditions that improves zero-shot generalization to other weather datasets.
Deformable DETR: Deformable transformers for end-to-end object detection
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VGGT-Occ embeds geometric tokens via PA-DA and uses sequential coarse-to-fine gated fusion to reach 33.00% IoU and 21.08% mIoU on SurroundOcc-nuScenes while using only ~41M parameters in the occupancy head.
citing papers explorer
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XWOD: A Real-World Benchmark for Object Detection under Extreme Weather Conditions
XWOD is a large-scale real-world benchmark for traffic object detection under seven extreme weather conditions that improves zero-shot generalization to other weather datasets.
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VGGT-Occ: Geometry-Grounded and Density-Aware Gated Fusion for 3D Occupancy Prediction
VGGT-Occ embeds geometric tokens via PA-DA and uses sequential coarse-to-fine gated fusion to reach 33.00% IoU and 21.08% mIoU on SurroundOcc-nuScenes while using only ~41M parameters in the occupancy head.