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 1421–1430 of 1723 papers

TitleStatusHype
Reasoning with shapes: profiting cognitive susceptibilities to infer linear mapping transformations between shapes—0
Recent Advances in Multi-modal 3D Scene Understanding: A Comprehensive Survey and Evaluation—0
Recognizing Dynamic Scenes with Deep Dual Descriptor based on Key Frames and Key Segments—0
Recognizing Material Properties from Images—0
Reconstructing Animals and the Wild—0
Reconstructing Vechicles from a Single Image: Shape Priors for Road Scene Understanding—0
Recyclable Semi-supervised Method Based on Multi-model Ensemble for Video Scene Parsing—0
Reducing Label Dependency for Underwater Scene Understanding: A Survey of Datasets, Techniques and Applications—0
Referring Self-supervised Learning on 3D Point Cloud—0
RefineCap: Concept-Aware Refinement for Image Captioning—0
Show:102550
← PrevPage 143 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