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 1271–1280 of 1723 papers

TitleStatusHype
ALFWorld: Aligning Text and Embodied Environments for Interactive LearningCode1
Weakly Supervised Learning of Multi-Object 3D Scene Decompositions Using Deep Shape Priors—0
Semi-Supervised Learning for Multi-Task Scene Understanding by Neural Graph ConsensusCode0
MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene UnderstandingCode1
Semi-Supervised Learning of Multi-Object 3D Scene Representations—0
Learning Category- and Instance-Aware Pixel Embedding for Fast Panoptic Segmentation—0
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
Towards General Purpose Geometry-Preserving Single-View Depth Estimation—0
Interactive Learning for Semantic Segmentation in Earth ObservationCode0
BoMuDANet: Unsupervised Adaptation for Visual Scene Understanding in Unstructured Driving EnvironmentsCode1
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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