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 831–840 of 1723 papers

TitleStatusHype
MOSE: Monocular Semantic Reconstruction Using NeRF-Lifted Noisy Priors—0
AVD2: Accident Video Diffusion for Accident Video Description—0
Identifying First-person Camera Wearers in Third-person Videos—0
Localization Guided Learning for Pedestrian Attribute Recognition—0
AmodalSynthDrive: A Synthetic Amodal Perception Dataset for Autonomous Driving—0
Movies2Scenes: Using Movie Metadata to Learn Scene Representation—0
DAWN: Vehicle Detection in Adverse Weather Nature Dataset—0
Long Range Pooling for 3D Large-Scale Scene Understanding—0
Monocular Depth Estimation with Sharp Boundary—0
Data-Driven Scene Understanding with Adaptively Retrieved Exemplars—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