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 1611–1620 of 1723 papers

Title	Date	Tasks	Status	Hype
Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras	Mar 26, 2017	Scene UnderstandingSegmentation	—Unverified	0
Predicting Deeper into the Future of Semantic Segmentation	Mar 22, 2017	AttributeAutonomous Driving	CodeCode Available	0
Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments	Mar 21, 2017	Motion PlanningScene Understanding	—Unverified	0
DA-RNN: Semantic Mapping with Data Associated Recurrent Neural Networks	Mar 9, 2017	Scene Understanding	CodeCode Available	0
Visual Translation Embedding Network for Visual Relation Detection	Feb 27, 2017	Objectobject-detection	CodeCode Available	0
Boundary-Seeking Generative Adversarial Networks	Feb 27, 2017	Scene UnderstandingText Generation	CodeCode Available	0
Recognizing Dynamic Scenes with Deep Dual Descriptor based on Key Frames and Key Segments	Feb 15, 2017	Scene RecognitionScene Understanding	—Unverified	0
ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes	Feb 14, 2017	3D Object ClassificationGeneral Classification	CodeCode Available	1
Joint 2D-3D-Semantic Data for Indoor Scene Understanding	Feb 3, 2017	Scene Understanding	CodeCode Available	1
Algorithmic Performance-Accuracy Trade-off in 3D Vision Applications Using HyperMapper	Feb 2, 2017	Active LearningGPU	—Unverified	0

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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