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 461–470 of 1723 papers

TitleStatusHype
CamContextI2V: Context-aware Controllable Video GenerationCode1
You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene UnderstandingCode1
From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object DetectionCode1
ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D DataCode1
3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene UnderstandingCode1
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth EstimationCode1
Segmenting Known Objects and Unseen Unknowns without Prior KnowledgeCode1
Pose-based Modular Network for Human-Object Interaction DetectionCode1
RGB-T Semantic Segmentation with Location, Activation, and SharpeningCode1
STRAP: Structured Object Affordance Segmentation with Point SupervisionCode1
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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