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 1526–1550 of 1723 papers

TitleStatusHype
The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes—0
The Right (Angled) Perspective: Improving the Understanding of Road Scenes Using Boosted Inverse Perspective Mapping—0
These Magic Moments: Differentiable Uncertainty Quantification of Radiance Field Models—0
-MRF: Capturing Spatial and Semantic Structure in the Parameters for Scene Understanding—0
The toulouse vanishing points dataset—0
What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies—0
An Exemplar-based CRF for Multi-instance Object Segmentation—0
What do We Learn by Semantic Scene Understanding for Remote Sensing imagery in CNN framework?—0
TinyRS-R1: Compact Multimodal Language Model for Remote Sensing—0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation—0
A New Ratio Image Based CNN Algorithm For SAR Despeckling—0
TopoMask: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture—0
TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module—0
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice—0
An Enhanced Object Detection Model for Scene Graph Generation—0
Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning—0
Toward Explainable and Fine-Grained 3D Grounding through Referring Textual Phrases—0
Towards 3D Scene Understanding by Referring Synthetic Models—0
An Enhanced Classification Method Based on Adaptive Multi-Scale Fusion for Long-tailed Multispectral Point Clouds—0
Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations—0
360+x: A Panoptic Multi-modal Scene Understanding Dataset—0
Towards A Unified Agent with Foundation Models—0
360^ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer—0
Towards Deeper and Better Multi-view Feature Fusion for 3D Semantic Segmentation—0
An Anti-fraud System for Car Insurance Claim Based on Visual Evidence—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