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 1651–1660 of 1723 papers

TitleStatusHype
Holistic 3D Scene Understanding From a Single Geo-Tagged Image—0
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset—0
Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense—0
Extracting Zero-shot Common Sense from Large Language Models for Robot 3D Scene Understanding—0
Holistic Understanding of 3D Scenes as Universal Scene Description—0
HSI-Drive v2.0: More Data for New Challenges in Scene Understanding for Autonomous Driving—0
HSPACE: Synthetic Parametric Humans Animated in Complex Environments—0
HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting—0
Human Action Recognition in Still Images Using ConViT—0
Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection—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