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 726–750 of 1723 papers

TitleStatusHype
Interactive Occlusion Boundary Estimation through Exploitation of Synthetic Data—0
Interpretable End-to-End Driving Model for Implicit Scene Understanding—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds—0
Incorporating Scene Context and Object Layout into Appearance Modeling—0
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods,Datasets,and Future Directions—0
Incorporating Explanations into Human-Machine Interfaces for Trust and Situation Awareness in Autonomous Vehicles—0
iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability—0
A Multi-purpose Realistic Haze Benchmark with Quantifiable Haze Levels and Ground Truth—0
Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding—0
InCoRo: In-Context Learning for Robotics Control with Feedback Loops—0
J-MOD^2: Joint Monocular Obstacle Detection and Depth Estimation—0
Deep Learned Full-3D Object Completion from Single View—0
Improving Online Lane Graph Extraction by Object-Lane Clustering—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Joint Optical Flow and Temporally Consistent Semantic Segmentation—0
Joint prototype and coefficient prediction for 3D instance segmentation—0
A Weakly-Supervised Depth Estimation Network Using Attention Mechanism—0
Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation—0
Improving Human-Object Interaction Detection via Phrase Learning and Label Composition—0
3D Pose Regression using Convolutional Neural Networks—0
Improving Building Segmentation for Off-Nadir Satellite Imagery—0
Kestrel: Point Grounding Multimodal LLM for Part-Aware 3D Vision-Language Understanding—0
Improving 6D Object Pose Estimation of metallic Household and Industry Objects—0
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation—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