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 1011–1020 of 1723 papers

Title	Date	Tasks	Status	Hype
Self-Supervised Road Layout Parsing with Graph Auto-Encoding	Mar 21, 2022	Image ReconstructionScene Understanding	CodeCode Available	0
Towards 3D Scene Understanding by Referring Synthetic Models	Mar 20, 2022	Scene UnderstandingTransfer Learning	—Unverified	0
Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows	Mar 20, 2022	Human-Object Interaction DetectionObject	—Unverified	0
Deep Point Cloud Simplification for High-quality Surface Reconstruction	Mar 17, 2022	Scene UnderstandingSurface Reconstruction	—Unverified	0
MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-based Visual Question Answering	Mar 17, 2022	Implicit RelationsQuestion Answering	CodeCode Available	1
Neural Part Priors: Learning to Optimize Part-Based Object Completion in RGB-D Scans	Mar 17, 2022	3D Object Recognitionglobal-optimization	—Unverified	0
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection	Mar 16, 2022	3D Object DetectionMonocular 3D Object Detection	CodeCode Available	1
Deep learning for radar data exploitation of autonomous vehicle	Mar 15, 2022	Autonomous DrivingDeep Learning	CodeCode Available	1
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding	Mar 15, 2022	Boundary DetectionHuman Parsing	CodeCode Available	2
RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry	Mar 14, 2022	Monocular Visual OdometryMotion Estimation	—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