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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1221–1230 of 1723 papers

TitleStatusHype
So you think you can track?—0
SparseLGS: Sparse View Language Embedded Gaussian Splatting—0
SPARTUN3D: Situated Spatial Understanding of 3D World in Large Language Models—0
SpatialLM: Training Large Language Models for Structured Indoor Modeling—0
Spatial Sampling Network for Fast Scene Understanding—0
Spatiotemporal Event Graphs for Dynamic Scene Understanding—0
Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data—0
SpectralGaussians: Semantic, spectral 3D Gaussian splatting for multi-spectral scene representation, visualization and analysis—0
SpeedMachines: Anytime Structured Prediction—0
Spherical World-Locking for Audio-Visual Localization in Egocentric Videos—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