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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1541–1550 of 1723 papers

Title	Date	Tasks	Status	Hype
EML-NET:An Expandable Multi-Layer NETwork for Saliency Prediction	May 2, 2018	Saliency PredictionScene Understanding	—Unverified	0
An Anti-fraud System for Car Insurance Claim Based on Visual Evidence	Apr 30, 2018	Scene Understanding	—Unverified	0
On the iterative refinement of densely connected representation levels for semantic segmentation	Apr 30, 2018	Image SegmentationScene Understanding	CodeCode Available	0
Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data	Apr 24, 2018	Data AugmentationScene Understanding	—Unverified	0
Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery	Apr 23, 2018	3D ReconstructionDepth Estimation	—Unverified	0
VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry	Apr 23, 2018	Outdoor LocalizationScene Understanding	—Unverified	0
LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics	Apr 16, 2018	NavigateScene Understanding	CodeCode Available	0
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation	Apr 12, 2018	Optical Flow EstimationScene Flow Estimation	CodeCode Available	0
Learning Depth from Single Images with Deep Neural Network Embedding Focal Length	Mar 27, 2018	Depth EstimationNetwork Embedding	—Unverified	0
DeepScores -- A Dataset for Segmentation, Detection and Classification of Tiny Objects	Mar 27, 2018	General ClassificationObject	CodeCode Available	1

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All datasets Semantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K val Semantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.44	—	Unverified
2	Team VGAI (TCS Research)	OMQ	0.37	—	Unverified
3	Demo_semantic_SLAM	OMQ	0.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CPN(ResNet-101)	Mean IoU	46.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACRV Baseline	OMQ	0.35	—	Unverified