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 1621–1630 of 1723 papers

Title	Date	Tasks	Status
Surgical Scene Segmentation by Transformer With Asymmetric Feature Enhancement	Oct 23, 2024	AnatomyScene Segmentation	CodeCode Available
Constructing a Visual Relationship Authenticity Dataset	Oct 11, 2020	Relationship DetectionScene Understanding	CodeCode Available
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding	Dec 22, 2022	Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATION	CodeCode Available
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond Aberrations	Nov 21, 2022	Domain AdaptationScene Understanding	CodeCode Available
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene Understanding	Apr 18, 2025	Deep LearningPoint Cloud Completion	CodeCode Available
Flow-based GAN for 3D Point Cloud Generation from a Single Image	Oct 8, 2022	Point Cloud GenerationScene Understanding	CodeCode Available
Scene Graph Generation from Objects, Phrases and Region Captions	Jul 31, 2017	Graph Generationobject-detection	CodeCode Available
Fine-Grained is Too Coarse: A Novel Data-Centric Approach for Efficient Scene Graph Generation	May 30, 2023	Graph GenerationImage Generation	CodeCode Available
Auxiliary Tasks in Multi-task Learning	May 16, 2018	Depth EstimationMulti-Task Learning	CodeCode Available
Auto-Embedding Generative Adversarial Networks for High Resolution Image Synthesis	Mar 27, 2019	Generative Adversarial NetworkImage Generation	CodeCode Available

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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