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 1521–1530 of 1723 papers

TitleStatusHype
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators—0
Unified Perceptual Parsing for Scene UnderstandingCode1
A Reinforcement Learning Approach to Target Tracking in a Camera Network—0
Three for one and one for three: Flow, Segmentation, and Surface NormalsCode0
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization—0
Visual Affordance and Function Understanding: A Survey—0
Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoningCode1
A Reflectance Based Method For Shadow Detection and Removal—0
End-to-End Race Driving with Deep Reinforcement Learning—0
A Survey of Knowledge Representation in Service Robotics—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