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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 741–750 of 1723 papers

TitleStatusHype
Large Language Models (LLMs) as Traffic Control Systems at Urban Intersections: A New Paradigm—0
MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth EstimationCode0
Content-Aware Preserving Image Generation—0
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
UniRiT: Towards Few-Shot Non-Rigid Point Cloud Registration—0
Symbolic Graph Inference for Compound Scene Understanding—0
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin-based Scene Representation—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