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 1591–1600 of 1723 papers

TitleStatusHype
Deep Scene Text Detection with Connected Component Proposals—0
BlitzNet: A Real-Time Deep Network for Scene UnderstandingCode0
Fast Scene Understanding for Autonomous DrivingCode0
Semantic Augmented Reality Environment with Material-Aware Physical Interactions—0
Dual-Glance Model for Deciphering Social RelationshipsCode0
Scene Graph Generation from Objects, Phrases and Region CaptionsCode0
Relationship Proposal Networks—0
Deep Video Deblurring for Hand-Held CamerasCode0
Weakly Supervised Affordance DetectionCode0
Neural Scene De-Rendering—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