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 781–790 of 1723 papers

TitleStatusHype
Learning Depth from Single Images with Deep Neural Network Embedding Focal Length—0
Learning Direct Optimization for Scene Understanding—0
Deep Contextual Attention for Human-Object Interaction Detection—0
DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding—0
Image-Graph-Image Translation via Auto-Encoding—0
Learning Geometric-Aware Properties in 2D Representation Using Lightweight CAD Models, or Zero Real 3D Pairs—0
A model of saliency-based visual attention for rapid scene analysis—0
Manhattan Scene Understanding via XSlit Imaging—0
Learning in Audio-visual Context: A Review, Analysis, and New Perspective—0
MaskAttn-UNet: A Mask Attention-Driven Framework for Universal Low-Resolution Image 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