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 1111–1120 of 1723 papers

TitleStatusHype
Lightweight integration of 3D features to improve 2D image segmentationCode0
Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation—0
Cross-Domain Synthetic-to-Real In-the-Wild Depth and Normal Estimation for 3D Scene Understanding—0
Gaussian Radar Transformer for Semantic Segmentation in Noisy Radar Data—0
Framework for 2D Ad placements in LinearTV—0
3D Object Aided Self-Supervised Monocular Depth Estimation—0
Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding—0
Prediction of Scene Plausibility—0
SGDraw: Scene Graph Drawing Interface Using Object-Oriented RepresentationCode0
Task-Aware Asynchronous Multi-Task Model with Class Incremental Contrastive Learning for Surgical Scene UnderstandingCode0
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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