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 1131–1140 of 1723 papers

TitleStatusHype
Learning from Maps: Visual Common Sense for Autonomous Driving—0
Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation—0
Learning Geometric-Aware Properties in 2D Representation Using Lightweight CAD Models, or Zero Real 3D Pairs—0
Learning in Audio-visual Context: A Review, Analysis, and New Perspective—0
SceneFun3D: Fine-Grained Functionality and Affordance Understanding in 3D Scenes—0
SceneGPT: A Language Model for 3D Scene Understanding—0
Scene Graph Generation: A Comprehensive Survey—0
A Comprehensive Survey of Scene Graphs: Generation and Application—0
Scene Image is Non-Mutually Exclusive - A Fuzzy Qualitative Scene Understanding—0
Scene-Independent Group Profiling in Crowd—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