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 1041–1050 of 1723 papers

TitleStatusHype
Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery—0
OpenGS-SLAM: Open-Set Dense Semantic SLAM with 3D Gaussian Splatting for Object-Level Scene Understanding—0
Deep Contextual Attention for Human-Object Interaction Detection—0
OpenLex3D: A New Evaluation Benchmark for Open-Vocabulary 3D Scene Representations—0
DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding—0
Large Scale Joint Semantic Re-Localisation and Scene Understanding via Globally Unique Instance Coordinate Regression—0
Open-RGBT: Open-vocabulary RGB-T Zero-shot Semantic Segmentation in Open-world Environments—0
OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene Datasets—0
OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets—0
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—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