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 1591–1600 of 1723 papers

TitleStatusHype
Generating Robot Constitutions & Benchmarks for Semantic Safety—0
FMGS: Foundation Model Embedded 3D Gaussian Splatting for Holistic 3D Scene Understanding—0
Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis—0
Generative Video Transformer: Can Objects be the Words?—0
FlowCaps: Optical Flow Estimation with Capsule Networks For Action Recognition—0
Geometric Constrained Non-Line-of-Sight Imaging—0
Geometric Constraints in Deep Learning Frameworks: A Survey—0
GeomGS: LiDAR-Guided Geometry-Aware Gaussian Splatting for Robot Localization—0
Floorplan-SLAM: A Real-Time, High-Accuracy, and Long-Term Multi-Session Point-Plane SLAM for Efficient Floorplan Reconstruction—0
Glass Segmentation Using Intensity and Spectral Polarization Cues—0
Show:102550
← PrevPage 160 of 173Next →
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