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 1311–1320 of 1723 papers

TitleStatusHype
TS40K: a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission System—0
Two Stream Scene Understanding on Graph Embedding—0
U4D: Unsupervised 4D Dynamic Scene Understanding—0
RemoteNet: Remote Sensing Image Segmentation Network based on Global-Local Information—0
Understanding and Evaluating Hallucinations in 3D Visual Language Models—0
Understanding Bayesian Rooms Using Composite 3D Object Models—0
Understanding Indoor Scenes Using 3D Geometric Phrases—0
Understanding Pedestrian Behaviors From Stationary Crowd Groups—0
Understanding Real World Indoor Scenes With Synthetic Data—0
Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks—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