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 401–410 of 1723 papers

Title	Date	Tasks	Status	Hype
Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments	Dec 8, 2020	Camera RelocalizationRobot Navigation	CodeCode Available	1
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding	Dec 5, 2020	image-classificationImage Classification	CodeCode Available	1
Understanding Bird's-Eye View of Road Semantics using an Onboard Camera	Dec 5, 2020	Autonomous NavigationAutonomous Vehicles	CodeCode Available	1
Towards Part-Based Understanding of RGB-D Scans	Dec 3, 2020	3D Instance SegmentationInstance Segmentation	CodeCode Available	1
Group Contextual Encoding for 3D Point Clouds	Dec 1, 2020	Scene Understanding	CodeCode Available	1
RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction	Nov 30, 2020	3D geometryObject	CodeCode Available	1
Visual place recognition: A survey from deep learning perspective	Nov 28, 2020	Deep LearningLoop Closure Detection	CodeCode Available	1
RELLIS-3D Dataset: Data, Benchmarks and Analysis	Nov 17, 2020	3D Semantic SegmentationAutonomous Navigation	CodeCode Available	1
SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments	Nov 9, 2020	Autonomous DrivingDepth Estimation	CodeCode Available	1
Towards Efficient Scene Understanding via Squeeze Reasoning	Nov 6, 2020	Instance Segmentationobject-detection	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