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 1621–1630 of 1723 papers

TitleStatusHype
Boundary-Seeking Generative Adversarial NetworksCode0
Visual Translation Embedding Network for Visual Relation DetectionCode0
Recognizing Dynamic Scenes with Deep Dual Descriptor based on Key Frames and Key Segments—0
Algorithmic Performance-Accuracy Trade-off in 3D Vision Applications Using HyperMapper—0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
Incremental Learning for Robot Perception through HRI—0
Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks—0
SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground TruthCode0
Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition—0
Deep Video DeblurringCode0
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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