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 301–310 of 1723 papers

Title	Date	Tasks	Status	Hype
Uncertainty-aware Panoptic Segmentation	Jun 29, 2022	Panoptic SegmentationScene Understanding	CodeCode Available	1
MGNet: Monocular Geometric Scene Understanding for Autonomous Driving	Jun 27, 2022	Autonomous DrivingDepth Estimation	CodeCode Available	1
IBISCape: A Simulated Benchmark for multi-modal SLAM Systems Evaluation in Large-scale Dynamic Environments	Jun 27, 2022	Autonomous VehiclesScene Segmentation	CodeCode Available	1
Panoramic Panoptic Segmentation: Insights Into Surrounding Parsing for Mobile Agents via Unsupervised Contrastive Learning	Jun 21, 2022	Contrastive LearningDomain Generalization	CodeCode Available	1
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and Reasoning	May 31, 2022	Common Sense ReasoningGraph Generation	CodeCode Available	1
Spatiality-guided Transformer for 3D Dense Captioning on Point Clouds	Apr 22, 2022	3D dense captioning3D Object Detection	CodeCode Available	1
P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior	Apr 5, 2022	Depth EstimationMonocular Depth Estimation	CodeCode Available	1
Online panoptic 3D reconstruction as a Linear Assignment Problem	Apr 1, 2022	3D ReconstructionImage Segmentation	CodeCode Available	1
Point Scene Understanding via Disentangled Instance Mesh Reconstruction	Mar 31, 2022	RetrievalScene Understanding	CodeCode Available	1
Collaborative Transformers for Grounded Situation Recognition	Mar 30, 2022	Grounded Situation RecognitionImage Classification	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