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 926–950 of 1723 papers

TitleStatusHype
Digital Divides in Scene Recognition: Uncovering Socioeconomic Biases in Deep Learning Systems—0
Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends—0
UniRiT: Towards Few-Shot Non-Rigid Point Cloud Registration—0
Multi-Model Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation—0
Multi-Object Classification and Unsupervised Scene Understanding Using Deep Learning Features and Latent Tree Probabilistic Models—0
DiffusionMTL: Learning Multi-Task Denoising Diffusion Model from Partially Annotated Data—0
A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding—0
Multiple-gaze geometry: Inferring novel 3D locations from gazes observed in monocular video—0
ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception—0
Diffusion Models in 3D Vision: A Survey—0
Diffusion-based RGB-D Semantic Segmentation with Deformable Attention Transformer—0
Multi-task GANs for Semantic Segmentation and Depth Completion with Cycle Consistency—0
Unsupervised 3D Structure Inference from Category-Specific Image Collections—0
DiffSDFSim: Differentiable Rigid-Body Dynamics With Implicit Shapes—0
Multi-Task Learning for Automotive Foggy Scene Understanding via Domain Adaptation to an Illumination-Invariant Representation—0
Multi-Task Learning for Visual Scene Understanding—0
Multi-task learning from fixed-wing UAV images for 2D/3D city modeling—0
Multi-Task Learning with Multi-Task Optimization—0
Unsupervised Discovery and Composition of Object Light Fields—0
Dietary Assessment with Multimodal ChatGPT: A Systematic Analysis—0
Multiview Based 3D Scene Understanding On Partial Point Sets—0
Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras—0
Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset—0
Multi-view PointNet for 3D Scene Understanding—0
Diagnostics in Semantic 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