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SotA/Computer Vision/Scene Understanding

Scene Understanding

52 benchmarks1723 papers

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Benchmarks

Scene Understanding on Cityscapes val

Scene Understanding on Stanford2D3D Panoramic

3DIoU Corner Error Pixel Error

Scene Understanding on VRD Relationship Detection

Scene Understanding on VRD Phrase Detection

Scene Understanding on VRD Predicate Detection

Scene Understanding on CamVid

Scene Understanding on PanoContext

Scene Understanding on VSPW

Scene Understanding on LaRS

Scene Understanding on Multispectral Video Semantic Segmentation

Scene Understanding on Semantic Scene Understanding Challenge (passive actuation & ground-truth localisation)

OMQ avg_pairwise avg_label avg_spatial avg_fp_quality

Scene Understanding on ImageNet-VidVRD

Recall@100 Recall@50 mAP

Scene Understanding on SoccerNet-v2

Scene Understanding on VidOR

Recall@100 Recall@50 mAP

Scene Understanding on ADE20K val

Scene Understanding on SUN360

Median Relighting Error

Scene Understanding on Semantic Scene Understanding Challenge (active actuation & ground-truth localisation)

OMQ avg_pairwise avg_label avg_spatial avg_fp_quality

Scene Understanding on VRD

Scene Understanding on Visual Genome

R@100 R@50 mR@100 mR@50

Scene Understanding on Argoverse

Scene Understanding on KITTI2012

Scene Understanding on Kitti Odometry

Scene Understanding on Kitti Raw

Scene Understanding on Realtor360