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 1701–1710 of 1723 papers

TitleStatusHype
SpeedMachines: Anytime Structured Prediction—0
Visual-Semantic Scene Understanding by Sharing Labels in a Context Network—0
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations—0
Cognitive Interpretation of Everyday Activities: Toward Perceptual Narrative Based Visuo-Spatial Scene Interpretation—0
Manhattan Scene Understanding via XSlit Imaging—0
Hallucinated Humans as the Hidden Context for Labeling 3D Scenes—0
Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs—0
Understanding Indoor Scenes Using 3D Geometric Phrases—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
Understanding Bayesian Rooms Using Composite 3D Object Models—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