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 626–650 of 1723 papers

TitleStatusHype
An Intelligent Safety System for Human-Centered Semi-Autonomous Vehicles—0
Distillation of Human-Object Interaction Contexts for Action Recognition—0
3D-RCNN: Instance-Level 3D Object Reconstruction via Render-and-Compare—0
BLOS-BEV: Navigation Map Enhanced Lane Segmentation Network, Beyond Line of Sight—0
3D-Grounded Vision-Language Framework for Robotic Task Planning: Automated Prompt Synthesis and Supervised Reasoning—0
Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows—0
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition—0
Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization—0
An Exemplar-based CRF for Multi-instance Object Segmentation—0
Disaster Anomaly Detector via Deeper FCDDs for Explainable Initial Responses—0
BlindSpotNet: Seeing Where We Cannot See—0
Adapting to Length Shift: FlexiLength Network for Trajectory Prediction—0
iReason: Multimodal Commonsense Reasoning using Videos and Natural Language with Interpretability—0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation—0
Direction-Aware Semi-Dense SLAM—0
Blending Learning and Inference in Structured Prediction—0
DINeMo: Learning Neural Mesh Models with no 3D Annotations—0
A New Ratio Image Based CNN Algorithm For SAR Despeckling—0
J-MOD^2: Joint Monocular Obstacle Detection and Depth Estimation—0
Audio-Visual Collaborative Representation Learning for Dynamic Saliency Prediction—0
Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems—0
Active Scene Understanding via Online Semantic Reconstruction—0
3D Question Answering for City Scene Understanding—0
DiffusionMTL: Learning Multi-Task Denoising Diffusion Model from Partially Annotated Data—0
Diffusion Models in 3D Vision: A Survey—0
Show:102550
← PrevPage 26 of 69Next →
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