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 721–730 of 1723 papers

TitleStatusHype
Learning Spatial Common Sense with Geometry-Aware Recurrent Networks—0
Learning to Interpret and Describe Abstract Scenes—0
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction—0
Lifting GIS Maps into Strong Geometric Context for Scene Understanding—0
Deep Point Cloud Simplification for High-quality Surface Reconstruction—0
Interactive Occlusion Boundary Estimation through Exploitation of Synthetic Data—0
InCoRo: In-Context Learning for Robotics Control with Feedback Loops—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds—0
Deep Learned Full-3D Object Completion from Single View—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