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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1521–1530 of 1723 papers

TitleStatusHype
Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions—0
Answerability Fields: Answerable Location Estimation via Diffusion Models—0
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation—0
The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes—0
An Intelligent Safety System for Human-Centered Semi-Autonomous Vehicles—0
The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes—0
The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping—0
These Magic Moments: Differentiable Uncertainty Quantification of Radiance Field Models—0
-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding—0
The toulouse vanishing points dataset—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