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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1441–1450 of 1723 papers

TitleStatusHype
A New Ratio Image Based CNN Algorithm For SAR Despeckling—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Panoptic Edge Detection—0
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Neural RGB(r)D Sensing: Depth and Uncertainty From a Video Camera—0
Towards Scene Understanding: Unsupervised Monocular Depth Estimation With Semantic-Aware Representation—0
Distraction-Aware Shadow Detection—0
Not Using the Car to See the Sidewalk -- Quantifying and Controlling the Effects of Context in Classification and Segmentation—0
Learning to Detect Human-Object Interactions With Knowledge—0
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from VideoCode0
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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