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 1451–1460 of 1723 papers

TitleStatusHype
Implicit Background Estimation for Semantic SegmentationCode0
Spatial Sampling Network for Fast Scene Understanding—0
Bridging Stereo Matching and Optical Flow via Spatiotemporal CorrespondenceCode0
Real-time Approximate Bayesian Computation for Scene Understanding—0
Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial ImagesCode0
A Joint Convolutional Neural Networks and Context Transfer for Street Scenes Labeling—0
An Information-Theoretic Metric of Transferability for Task Transfer LearningCode0
Reasoning About Physical Interactions with Object-Centric Models—0
Segmenting the FutureCode0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation—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