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 1121–1130 of 1723 papers

TitleStatusHype
Combining Implicit-Explicit View Correlation for Light Field Semantic Segmentation—0
Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks—0
4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding—0
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties—0
PhysPose: Refining 6D Object Poses with Physical Constraints—0
Picture: A Probabilistic Programming Language for Scene Perception—0
CoMatcher: Multi-View Collaborative Feature Matching—0
Cognitive Interpretation of Everyday Activities: Toward Perceptual Narrative Based Visuo-Spatial Scene Interpretation—0
Places: An Image Database for Deep Scene Understanding—0
COFGA: Classification Of Fine-Grained Features In Aerial Images—0
Show:102550
← PrevPage 113 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