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 1101–1110 of 1723 papers

TitleStatusHype
Visual Traffic Knowledge Graph Generation from Scene Images—0
Plausible Uncertainties for Human Pose Regression—0
Self-Supervised Object Detection from Egocentric Videos—0
Learning Geometric-Aware Properties in 2D Representation Using Lightweight CAD Models, or Zero Real 3D Pairs—0
Combining Implicit-Explicit View Correlation for Light Field Semantic Segmentation—0
RealGraph: A Multiview Dataset for 4D Real-world Context Graph Generation—0
Attentional Graph Convolutional Network for Structure-aware Audio-Visual Scene Classification—0
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene UnderstandingCode0
MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency—0
METEOR Guided Divergence for Video CaptioningCode0
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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