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 801–825 of 1723 papers

TitleStatusHype
DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding—0
Image-Graph-Image Translation via Auto-Encoding—0
Learning to Detect Human-Object Interactions With Knowledge—0
Learning to Exploit Stability for 3D Scene Parsing—0
Learning to Interpret and Describe Abstract Scenes—0
A model of saliency-based visual attention for rapid scene analysis—0
Modeling Uncertainty in 3D Gaussian Splatting through Continuous Semantic Splatting—0
Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding—0
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—0
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction—0
Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization—0
An Exemplar-based CRF for Multi-instance Object Segmentation—0
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships—0
IM2CAD—0
Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation—0
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features—0
Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding—0
AVD2: Accident Video Diffusion for Accident Video Description—0
Lifting GIS Maps into Strong Geometric Context for Scene Understanding—0
MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency—0
Identifying First-person Camera Wearers in Third-person Videos—0
AmodalSynthDrive: A Synthetic Amodal Perception Dataset for Autonomous Driving—0
MNEW: Multi-domain Neighborhood Embedding and Weighting for Sparse Point Clouds Segmentation—0
LiveHPS: LiDAR-based Scene-level Human Pose and Shape Estimation in Free Environment—0
DAWN: Vehicle Detection in Adverse Weather Nature Dataset—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