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 801–810 of 1723 papers

TitleStatusHype
MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency—0
Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding—0
Learning to Detect Human-Object Interactions With Knowledge—0
Learning to Exploit Stability for 3D Scene Parsing—0
Learning to Interpret and Describe Abstract Scenes—0
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—0
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation—0
IM2CAD—0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features—0
MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning—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