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 1231–1240 of 1723 papers

Title	Date	Tasks	Status	Hype
Scene Text Detection for Augmented Reality -- Character Bigram Approach to reduce False Positive Rate	Dec 26, 2020	Scene Text DetectionScene Understanding	—Unverified	0
P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding	Dec 24, 2020	Contrastive LearningRepresentation Learning	—Unverified	0
Classification of Single-View Object Point Clouds	Dec 18, 2020	3D Object Classification6D Pose Estimation using RGB	—Unverified	0
Embodied Visual Active Learning for Semantic Segmentation	Dec 17, 2020	Active LearningDeep Reinforcement Learning	—Unverified	0
Event-based Motion Segmentation with Spatio-Temporal Graph Cuts	Dec 16, 2020	Motion SegmentationScene Understanding	CodeCode Available	1
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos	Dec 15, 2020	Autonomous VehiclesCamera Auto-Calibration	—Unverified	0
Image-Graph-Image Translation via Auto-Encoding	Dec 10, 2020	Scene UnderstandingTranslation	—Unverified	0
Competitive Simplicity for Multi-Task Learning for Real-Time Foggy Scene Understanding via Domain Adaptation	Dec 9, 2020	Depth EstimationDomain Adaptation	—Unverified	0
Multi-Model Learning for Real-Time Automotive Semantic Foggy Scene Understanding via Domain Adaptation	Dec 9, 2020	DecoderDomain Adaptation	—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