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 151–160 of 1723 papers

TitleStatusHype
OpenLex3D: A New Evaluation Benchmark for Open-Vocabulary 3D Scene Representations—0
SuperFlow++: Enhanced Spatiotemporal Consistency for Cross-Modal Data PretrainingCode2
The Coralscapes Dataset: Semantic Scene Understanding in Coral ReefsCode1
Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving—0
SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language PretrainingCode3
PanoGS: Gaussian-based Panoptic Segmentation for 3D Open Vocabulary Scene Understanding—0
MLLM-For3D: Adapting Multimodal Large Language Model for 3D Reasoning Segmentation—0
PolarFree: Polarization-based Reflection-free ImagingCode2
PanopticSplatting: End-to-End Panoptic Gaussian Splatting—0
Geometric Constrained Non-Line-of-Sight Imaging—0
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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