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 141–150 of 1723 papers

TitleStatusHype
NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language ModelsCode1
Logic-RAG: Augmenting Large Multimodal Models with Visual-Spatial Knowledge for Road Scene UnderstandingCode1
A Data-Centric Revisit of Pre-Trained Vision Models for Robot LearningCode1
VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene CompletionCode1
Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation CorrentropyCode1
Event-aided Semantic Scene CompletionCode1
EndoChat: Grounded Multimodal Large Language Model for Endoscopic SurgeryCode1
A Survey of World Models for Autonomous DrivingCode1
3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene UnderstandingCode1
All-Day Multi-Camera Multi-Target TrackingCode1
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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