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 1161–1170 of 1723 papers

TitleStatusHype
CI-Net: Contextual Information for Joint Semantic Segmentation and Depth Estimation—0
Probabilistic Future Prediction for Video Scene Understanding—0
ChatSplat: 3D Conversational Gaussian Splatting—0
ChatBEV: A Visual Language Model that Understands BEV Maps—0
ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimation—0
Prospective Role of Foundation Models in Advancing Autonomous Vehicles—0
Vision-Centric Representation-Efficient Fine-Tuning for Robust Universal Foreground Segmentation—0
PSDR-Room: Single Photo to Scene using Differentiable Rendering—0
Pseudo Label-Guided Multi Task Learning for Scene Understanding—0
PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation—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