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 1641–1650 of 1723 papers

TitleStatusHype
Adapting Deep Network Features to Capture Psychological RepresentationsCode0
Joint Optical Flow and Temporally Consistent Semantic Segmentation—0
Small-Variance Nonparametric Clustering on the Hypersphere—0
LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning—0
Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery—0
A Task-Oriented Approach for Cost-Sensitive Recognition—0
Understanding Real World Indoor Scenes With Synthetic Data—0
Occlusion Boundary Detection via Deep Exploration of Context—0
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Newtonian Scene Understanding: Unfolding the Dynamics of Objects in Static Images—0
Show:102550
← PrevPage 165 of 173Next →
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