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 341–350 of 1723 papers

TitleStatusHype
Content-Aware Preserving Image Generation—0
OSMLoc: Single Image-Based Visual Localization in OpenStreetMap with Fused Geometric and Semantic GuidanceCode2
SE(3) Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation—0
Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving—0
Modeling Uncertainty in 3D Gaussian Splatting through Continuous Semantic Splatting—0
Multi-task Geometric Estimation of Depth and Surface Normal from Monocular 360° ImagesCode0
On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDARCode2
Symbolic Graph Inference for Compound Scene Understanding—0
UniRiT: Towards Few-Shot Non-Rigid Point Cloud Registration—0
Senna: Bridging Large Vision-Language Models and End-to-End Autonomous DrivingCode4
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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