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 1401–1410 of 1723 papers

TitleStatusHype
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation—0
Q-GroundCAM: Quantifying Grounding in Vision Language Models via GradCAM—0
Quantifying the synthetic and real domain gap in aerial scene understanding—0
QueSTMaps: Queryable Semantic Topological Maps for 3D Scene Understanding—0
R3DS: Reality-linked 3D Scenes for Panoramic Scene Understanding—0
Radiation Search Operations using Scene Understanding with Autonomous UAV and UGV—0
Radiometric Scene Decomposition: Scene Reflectance, Illumination, and Geometry from RGB-D Images—0
RAFT: Robust Augmentation of FeaTures for Image Segmentation—0
RailSem19: A Dataset for Semantic Rail Scene Understanding—0
RangeSeg: Range-Aware Real Time Segmentation of 3D LiDAR Point Clouds—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