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 1401–1410 of 1723 papers

Title	Date	Tasks	Status
Addressing the Sim2Real Gap in Robotic 3D Object Classification	Oct 28, 2019	3D Object ClassificationClassification	—Unverified
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships	Oct 27, 2019	Graph GenerationRelationship Detection	—Unverified
GANspection	Oct 21, 2019	Scene Understanding	—Unverified
Deep Contextual Attention for Human-Object Interaction Detection	Oct 17, 2019	Human-Object Interaction DetectionObject	—Unverified
Deep Semantic Segmentation of Natural and Medical Images: A Review	Oct 16, 2019	Image SegmentationMedical Image Analysis	—Unverified
Semantic Understanding of Foggy Scenes with Purely Synthetic Data	Oct 9, 2019	Scene UnderstandingSelf-Driving Cars	CodeCode Available
Using Image Priors to Improve Scene Understanding	Oct 2, 2019	Autonomous DrivingAutonomous Vehicles	—Unverified
Real-Time Semantic Stereo Matching	Oct 1, 2019	Scene UnderstandingSemantic Segmentation	—Unverified
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection	Oct 1, 2019	RGB-D Salient Object DetectionSaliency Detection	CodeCode Available
Multi-view PointNet for 3D Scene Understanding	Sep 30, 2019	3D Instance Segmentation3D Semantic Segmentation	—Unverified

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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