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 1541–1550 of 1723 papers

TitleStatusHype
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning—0
Toward Explainable and Fine-Grained 3D Grounding through Referring Textual Phrases—0
Towards 3D Scene Understanding by Referring Synthetic Models—0
An Enhanced Classification Method Based on Adaptive Multi-Scale Fusion for Long-tailed Multispectral Point Clouds—0
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations—0
360+x: A Panoptic Multi-modal Scene Understanding Dataset—0
Towards A Unified Agent with Foundation Models—0
360^ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer—0
Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation—0
An Anti-fraud System for Car Insurance Claim Based on Visual Evidence—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