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 1031–1040 of 1723 papers

TitleStatusHype
AccidentBlip: Agent of Accident Warning based on MA-former—0
On the Pareto Efficiency of Quantized CNN—0
Deep Learning Techniques for Geospatial Data Analysis—0
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation—0
User Identification: A Key Enabler for Multi-User Vision-Aided Communications—0
On the usability of deep networks for object-based image analysis—0
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods,Datasets,and Future Directions—0
Open Challenges for Monocular Single-shot 6D Object Pose Estimation—0
Deep Learned Full-3D Object Completion from Single View—0
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation—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