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 731–740 of 1723 papers

TitleStatusHype
Temporal DINO: A Self-supervised Video Strategy to Enhance Action Prediction—0
Syn-Mediverse: A Multimodal Synthetic Dataset for Intelligent Scene Understanding of Healthcare Facilities—0
Scene-aware Human Pose Generation using Transformer—0
Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint PredictionCode0
Weakly Supervised 3D Instance Segmentation without Instance-level Annotations—0
Interpretable End-to-End Driving Model for Implicit Scene Understanding—0
Gated Driver Attention PredictorCode0
Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding—0
TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-ExpertsCode2
OAFuser: Towards Omni-Aperture Fusion for Light Field Semantic SegmentationCode1
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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