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 491–500 of 1723 papers

TitleStatusHype
Case-based Reasoning Augmented Large Language Model Framework for Decision Making in Realistic Safety-Critical Driving Scenarios—0
DreamAnywhere: Object-Centric Panoramic 3D Scene Generation—0
IPFormer: Visual 3D Panoptic Scene Completion with Context-Adaptive Instance Proposals—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
Scene-R1: Video-Grounded Large Language Models for 3D Scene Reasoning without 3D Annotations—0
SceneAware: Scene-Constrained Pedestrian Trajectory Prediction with LLM-Guided WalkabilityCode0
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
Unified Representation Space for 3D Visual Grounding—0
Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems—0
FreeQ-Graph: Free-form Querying with Semantic Consistent Scene Graph for 3D Scene Understanding—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