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 941–950 of 1723 papers

TitleStatusHype
Multi-Task Learning for Visual Scene Understanding—0
Multi-task learning from fixed-wing UAV images for 2D/3D city modeling—0
Multi-Task Learning with Multi-Task Optimization—0
Unsupervised Discovery and Composition of Object Light Fields—0
Dietary Assessment with Multimodal ChatGPT: A Systematic Analysis—0
Multiview Based 3D Scene Understanding On Partial Point Sets—0
Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras—0
Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset—0
Multi-view PointNet for 3D Scene Understanding—0
Diagnostics in Semantic Segmentation—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