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 1561–1570 of 1723 papers

TitleStatusHype
Object segmentation in depth maps with one user click and a synthetically trained fully convolutional network—0
Boundary Seeking GANs—0
Spatial As Deep: Spatial CNN for Traffic Scene UnderstandingCode0
Self-Supervised Relative Depth Learning for Urban Scene Understanding—0
Why my photos look sideways or upside down? Detecting Canonical Orientation of Images using Convolutional Neural Networks—0
Feature discovery and visualization of robot mission data using convolutional autoencoders and Bayesian nonparametric topic models—0
Small Drone Field Experiment: Data Collection & Processing—0
Grounded Objects and Interactions for Video Captioning—0
Natural Language Guided Visual Relationship Detection—0
HyKo: A Spectral Dataset for Scene Understanding—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