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 421–430 of 1723 papers

TitleStatusHype
Few-Shot Object Detection and Viewpoint Estimation for Objects in the WildCode1
ScanQA: 3D Question Answering for Spatial Scene UnderstandingCode1
A Data-Centric Revisit of Pre-Trained Vision Models for Robot LearningCode1
DPF: Learning Dense Prediction Fields with Weak SupervisionCode1
Boundary-induced and scene-aggregated network for monocular depth predictionCode1
ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D DataCode1
Self-distillation for surgical action recognitionCode1
PointVST: Self-Supervised Pre-training for 3D Point Clouds via View-Specific Point-to-Image TranslationCode1
Semantic Abstraction: Open-World 3D Scene Understanding from 2D Vision-Language ModelsCode1
3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene UnderstandingCode1
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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