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 1021–1030 of 1723 papers

TitleStatusHype
GeomGS: LiDAR-Guided Geometry-Aware Gaussian Splatting for Robot Localization—0
Glass Segmentation Using Intensity and Spectral Polarization Cues—0
Global Context Aware Convolutions for 3D Point Cloud Understanding—0
GOI: Find 3D Gaussians of Interest with an Optimizable Open-vocabulary Semantic-space Hyperplane—0
Going Beyond Multi-Task Dense Prediction with Synergy Embedding Models—0
GP-NeRF: Generalized Perception NeRF for Context-Aware 3D Scene Understanding—0
GPT-4V Explorations: Mining Autonomous Driving—0
GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction—0
GP-VLS: A general-purpose vision language model for surgery—0
Graph-Based Multi-Modal Sensor Fusion for Autonomous Driving—0
Show:102550
← PrevPage 103 of 173Next →
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