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 1321–1330 of 1723 papers

TitleStatusHype
Competitive Simplicity for Multi-Task Learning for Real-Time Foggy Scene Understanding via Domain Adaptation—0
Exploring Deep 3D Spatial Encodings for Large-Scale 3D Scene Understanding—0
Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency—0
The Devil is in the Boundary: Exploiting Boundary Representation for Basis-based Instance Segmentation—0
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments—0
FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
Learning Regional Purity for Instance Segmentation on 3D Point CloudsCode0
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds—0
Highway Driving Dataset for Semantic Video Segmentation—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