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

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Showing 751–760 of 1723 papers

TitleStatusHype
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation—0
A Multiple-View Geometric Model for Specularity Prediction on General Curved Surfaces—0
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds—0
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation—0
Living in a Material World: Learning Material Properties from Full-Waveform Flash Lidar Data for Semantic Segmentation—0
IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement—0
LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding—0
Image-to-Height Domain Translation for Synthetic Aperture Sonar—0
Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery—0
Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems—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