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 851–875 of 1723 papers

TitleStatusHype
Learning Segmented 3D Gaussians via Efficient Feature Unprojection for Zero-shot Neural Scene Segmentation—0
CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting—0
COUNT Forest: CO-Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation—0
Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving—0
Cross-modal Learning for Multi-modal Video Categorization—0
CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos—0
DAE-Fuse: An Adaptive Discriminative Autoencoder for Multi-Modality Image Fusion—0
DaF-BEVSeg: Distortion-aware Fisheye Camera based Bird's Eye View Segmentation with Occlusion Reasoning—0
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference—0
Data-Driven Scene Understanding with Adaptively Retrieved Exemplars—0
DAWN: Vehicle Detection in Adverse Weather Nature Dataset—0
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—0
DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding—0
Deep Contextual Attention for Human-Object Interaction Detection—0
Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery—0
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation—0
Deep Learned Full-3D Object Completion from Single View—0
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods,Datasets,and Future Directions—0
Deep Learning Techniques for Geospatial Data Analysis—0
Deeply Learned Attributes for Crowded Scene Understanding—0
Deep Optics for Monocular Depth Estimation and 3D Object Detection—0
Deep Point Cloud Simplification for High-quality Surface Reconstruction—0
Deep Robust Single Image Depth Estimation Neural Network Using Scene Understanding—0
Deep Scene Text Detection with Connected Component Proposals—0
Deep Semantic Segmentation of Natural and Medical Images: A Review—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