SOTAVerified

Scene Understanding

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.

Papers

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Showing 1361–1370 of 1723 papers

TitleStatusHype
VLP: Vision Language Planning for Autonomous Driving—0
VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding—0
VoteSplat: Hough Voting Gaussian Splatting for 3D Scene Understanding—0
vS-Graphs: Integrating Visual SLAM and Situational Graphs through Multi-level Scene Understanding—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
Weakly Supervised 3D Instance Segmentation without Instance-level Annotations—0
Weakly-Supervised 3D Visual Grounding based on Visual Linguistic Alignment—0
Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning—0
Weakly Supervised Learning of Affordances—0
Weakly Supervised Point Clouds Transformer for 3D Object Detection—0
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified