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 631–640 of 1723 papers

TitleStatusHype
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization—0
An Exemplar-based CRF for Multi-instance Object Segmentation—0
Disaster Anomaly Detector via Deeper FCDDs for Explainable Initial Responses—0
BlindSpotNet: Seeing Where We Cannot See—0
Adapting to Length Shift: FlexiLength Network for Trajectory Prediction—0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation—0
Direction-Aware Semi-Dense SLAM—0
Blending Learning and Inference in Structured Prediction—0
DINeMo: Learning Neural Mesh Models with no 3D Annotations—0
Show:102550
← PrevPage 64 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