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 1076–1100 of 1723 papers

TitleStatusHype
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
InCoRo: In-Context Learning for Robotics Control with Feedback Loops—0
Incorporating Explanations into Human-Machine Interfaces for Trust and Situation Awareness in Autonomous Vehicles—0
Incorporating Scene Context and Object Layout into Appearance Modeling—0
Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs—0
Incremental Learning for Robot Perception through HRI—0
Indoor Scene Understanding in 2.5/3D for Autonomous Agents: A Survey—0
Indoor Semantic Scene Understanding using Multi-modality Fusion—0
Inferring Shared Attention in Social Scene Videos—0
InLUT3D: Challenging real indoor dataset for point cloud analysis—0
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization—0
In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding—0
Input-Output Balanced Framework for Long-tailed LiDAR Semantic Segmentation—0
Instance- and Category-level 6D Object Pose Estimation—0
InstanceGaussian: Appearance-Semantic Joint Gaussian Representation for 3D Instance-Level Perception—0
Integrating LMM Planners and 3D Skill Policies for Generalizable Manipulation—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
Interactive Occlusion Boundary Estimation through Exploitation of Synthetic Data—0
Interpretable End-to-End Driving Model for Implicit Scene Understanding—0
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds—0
IPFormer: Visual 3D Panoptic Scene Completion with Context-Adaptive Instance Proposals—0
iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability—0
Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows—0
J-MOD^2: Joint Monocular Obstacle Detection and Depth Estimation—0
Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World—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