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 381–390 of 1723 papers

Title	Date	Tasks	Status	Hype
OvarNet: Towards Open-vocabulary Object Attribute Recognition	Jan 23, 2023	AttributeKnowledge Distillation	CodeCode Available	1
OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis	Jun 4, 2025	Action GenerationDecision Making	CodeCode Available	1
Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation	Jul 23, 2021	Domain AdaptationFew-Shot Learning	CodeCode Available	1
A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images	Feb 16, 2021	Decision MakingScene Understanding	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
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts	Dec 16, 2020	3D Semantic SegmentationInstance Segmentation	CodeCode Available	1
Bidirectional Projection Network for Cross Dimension Scene Understanding	Mar 26, 2021	2D Semantic Segmentation3D Semantic 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
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models	Oct 18, 2022	image-classificationImage Classification	CodeCode Available	1
Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous Driving	May 13, 2025	3D visual groundingAutonomous Driving	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