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 51–60 of 1723 papers

TitleStatusHype
Stag-1: Towards Realistic 4D Driving Simulation with Video Generation ModelCode2
EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene UnderstandingCode2
LSceneLLM: Enhancing Large 3D Scene Understanding Using Adaptive Visual PreferencesCode2
GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial TasksCode2
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion ModelsCode2
GaussianPretrain: A Simple Unified 3D Gaussian Representation for Visual Pre-training in Autonomous DrivingCode2
OSMLoc: Single Image-Based Visual Localization in OpenStreetMap with Fused Geometric and Semantic GuidanceCode2
On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDARCode2
VLM-Grounder: A VLM Agent for Zero-Shot 3D Visual GroundingCode2
ARKit LabelMaker: A New Scale for Indoor 3D Scene UnderstandingCode2
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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