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 861–870 of 1723 papers

TitleStatusHype
CEKD: Cross-Modal Edge-Privileged Knowledge Distillation for Semantic Scene Understanding Using Only Thermal ImagesCode1
Deep Learning for Event-based Vision: A Comprehensive Survey and BenchmarksCode1
Explicit3D: Graph Network with Spatial Inference for Single Image 3D Object Detection—0
3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose EstimationCode1
Object-Centric Scene Representations using Active Inference—0
Structured Generative Models for Scene Understanding—0
A Flexible Framework for Virtual Omnidirectional Vision to Improve Operator Situation Awareness—0
GALIP: Generative Adversarial CLIPs for Text-to-Image SynthesisCode2
Learning from Mistakes: Self-Regularizing Hierarchical Representations in Point Cloud Semantic Segmentation—0
OvarNet: Towards Open-vocabulary Object Attribute RecognitionCode1
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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