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 1281–1290 of 1723 papers

TitleStatusHype
Boosting Cross-spectral Unsupervised Domain Adaptation for Thermal Semantic Segmentation—0
BLOS-BEV: Navigation Map Enhanced Lane Segmentation Network, Beyond Line of Sight—0
SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis—0
Counterfactual Critic Multi-Agent Training for Scene Graph Generation—0
SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes—0
SceneGPT: A Language Model for 3D Scene Understanding—0
BlindSpotNet: Seeing Where We Cannot See—0
Scene Graph Generation: A Comprehensive Survey—0
ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding—0
A Comprehensive Survey of Scene Graphs: Generation and Application—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