mlsanityData to 14 Oct 2026

Style Transfer: From Stitching to Neural Networks

arXiv 2409.00606 ↗First posted 1 Sep 2024cs.CVcited by 8

Not on the map. Why?

Abstract (arXiv)

This article compares two style transfer methods in image processing: the traditional method, which synthesizes new images by stitching together small patches from existing images, and a modern machine learning-based approach that uses a segmentation network to isolate foreground objects and apply style transfer solely to the background. The traditional method excels in creating artistic abstractions but can struggle with seamlessness, whereas the machine learning method preserves the integrity of foreground elements while enhancing the background, offering improved aesthetic quality and computational efficiency. Our study indicates that machine learning-based methods are more suited for real-world applications where detail preservation in foreground elements is essential.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 42 of its 82 references that are in the map. First posted on arXiv 1 Sep 2024.

Builds on

42 of 82 references.

References · 42

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2015An Introduction to Convolutional Neural Networkscited by 514
  3. 2015A Neural Algorithm of Artistic Stylecited by 483
  4. 2020Deep Learning for Text Style Transfer: A Surveycited by 162
  5. 2024Survival Prediction Across Diverse Cancer Types Using Neural Networkscited by 80
  6. 2022Can Language Understand Depth?cited by 69
  7. 2023Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networkscited by 56
  8. 2024Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an examplecited by 50
  9. 2024Exploring Diverse Methods in Visual Question Answeringcited by 45
  10. 2018Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagerycited by 43
  11. 2024ComposerX: Multi-Agent Symbolic Music Composition with LLMscited by 42
  12. 2024Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformerscited by 35
30 more
  1. 2024WorDepth: Variational Language Prior for Monocular Depth Estimationcited by 34
  2. 2024Regional Style and Color Transfercited by 30
  3. 2024Credit Card Fraud Detection Using Advanced Transformer Modelcited by 26
  4. 2024Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approachcited by 24
  5. 2023Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstructioncited by 22
  6. 2024MMREC: LLM Based Multi-Modal Recommender Systemcited by 22
  7. 2024Towards Resilient and Efficient LLMs: A Comparative Study of Efficiency, Performance, and Adversarial Robustnesscited by 22
  8. 2019Confidence Trigger Detection: Accelerating Real-time Tracking-by-detection Systemscited by 21
  9. 2024A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentationcited by 21
  10. 2021An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Datasetcited by 18
  11. 2021DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusioncited by 17
  12. 2022A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesiscited by 16
  13. 2024Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methodscited by 16
  14. 2024Data Imputation using Large Language Model to Accelerate Recommendation Systemcited by 15
  15. 2023Influence Pathway Discovery on Social Mediacited by 11
  16. 2021An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivitiescited by 10
  17. 2024Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENNcited by 10
  18. 2024Advanced Payment Security System:XGBoost, LightGBM and SMOTE Integratedcited by 8
  19. 2024Multi-task Magnetic Resonance Imaging Reconstruction using Meta-learningcited by 7
  20. 2023Optimization-Based Deep learning methods for Magnetic Resonance Imaging Reconstruction and Synthesiscited by 5
  21. 2023Magnetic Resonance Parameter Mapping using Self-supervised Deep Learning with Model Reinforcementcited by 5
  22. 2023Federated cINN Clustering for Accurate Clustered Federated Learningcited by 4
  23. 2024A Review of Electromagnetic Elimination Methods for low-field portable MRI scannercited by 4
  24. 2021Using PPP Information to Implement a Global Real-Time Virtual Network DGNSS Approachcited by 3
  25. 2024Rethink Arbitrary Style Transfer with Transformer and Contrastive Learningcited by 3
  26. 2024Debiasing Machine Unlearning with Counterfactual Examplescited by 3
  27. 2024A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learningcited by 3
  28. 2021Performance analysis of facial recognition: A critical review through glass factorcited by 2
  29. 2024Outlier Accommodation for GNSS Precise Point Positioning using Risk-Averse State Estimationcited by 2
  30. 2024Optimization-Based Outlier Accommodation for Tightly Coupled RTK-Aided Inertial Navigation Systems in Urban Environmentscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 7; 2026: 1.

8 papers.

  1. 2025Data Augmentation Through Random Style Replacementcited by 9
  2. 2025Journey into Automation: Image-Derived Pavement Texture Extraction and Evaluationcited by 7
  3. 2025NeRF-Based defect detectioncited by 7
  4. 2025Anomaly Detection and Early Warning Mechanism for Intelligent Monitoring Systems in Multi-Cloud Environments Based on LLMcited by 1
  5. 2025DiffStyleTS: Diffusion Model for Style Transfer in Time Seriescited by 1
  6. 2025From Classification to Cross-Modal Understanding: Leveraging Vision-Language Models for Fine-Grained Renal Pathologycited by 1
  7. 2025Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platformscited by 0
  8. 2026Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly Detectioncited by 0