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 1231–1240 of 1723 papers

TitleStatusHype
SplatTalk: 3D VQA with Gaussian Splatting—0
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds—0
sshELF: Single-Shot Hierarchical Extrapolation of Latent Features for 3D Reconstruction from Sparse-Views—0
SSNet: Saliency Prior and State Space Model-based Network for Salient Object Detection in RGB-D Images—0
StandardSim: A Synthetic Dataset For Retail Environments—0
Stochastic Future Prediction in Real World Driving Scenarios—0
Str-L Pose: Integrating Point and Structured Line for Relative Pose Estimation in Dual-Graph—0
Semantic and structural image segmentation for prosthetic vision—0
Structural Concept Learning via Graph Attention for Multi-Level Rearrangement Planning—0
Structured agents for physical construction—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