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 351–360 of 1723 papers

TitleStatusHype
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin-based Scene Representation—0
Surgical Scene Segmentation by Transformer With Asymmetric Feature EnhancementCode0
PerspectiveNet: Multi-View Perception for Dynamic Scene Understanding—0
Large Language Models for Autonomous Driving (LLM4AD): Concept, Benchmark, Experiments, and Challenges—0
Part-Whole Relational Fusion Towards Multi-Modal Scene UnderstandingCode0
ARKit LabelMaker: A New Scale for Indoor 3D Scene UnderstandingCode2
VLM-Grounder: A VLM Agent for Zero-Shot 3D Visual GroundingCode2
SAM-Guided Masked Token Prediction for 3D Scene Understanding—0
3DArticCyclists: Generating Synthetic Articulated 8D Pose-Controllable Cyclist Data for Computer Vision Applications—0
LoLI-Street: Benchmarking Low-Light Image Enhancement and BeyondCode1
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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