# Locally-Focused Face Representation for Sketch-to-Image Generation Using Noise-Induced Refinement

arXiv: https://arxiv.org/abs/2411.19005 · HTML: https://mlsanity.com/paper/2411.19005/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 28 references that are in the map.
- First posted on arXiv 28 Nov 2024.

## Builds on (most cited first, 12 of 12)

- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs](https://mlsanity.com/paper/1711.11585/) (2017)
- [Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation](https://mlsanity.com/paper/2008.00951/) (2020)
- [MaskGAN: Towards Diverse and Interactive Facial Image Manipulation](https://mlsanity.com/paper/1907.11922/) (2019)
- [Towards Real-World Blind Face Restoration with Generative Facial Prior](https://mlsanity.com/paper/2101.04061/) (2021)
- [Generative Adversarial Perturbations](https://mlsanity.com/paper/1712.02328/) (2017)
- [SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis](https://mlsanity.com/paper/1801.02753/) (2018)
- [Unsupervised Sketch-to-Photo Synthesis](https://mlsanity.com/paper/1909.08313/) (2019)
- [Deep Generation of Face Images from Sketches](https://mlsanity.com/paper/2006.01047/) (2020)
- [LinesToFacePhoto: Face Photo Generation from Lines with Conditional Self-Attention Generative Adversarial Network](https://mlsanity.com/paper/1910.08914/) (2019)
- [Improving Sketch Colorization using Adversarial Segmentation Consistency](https://mlsanity.com/paper/2301.08590/) (2023)

## Built on by (most cited first, 3 of 3)

- [2D_3D Feature Fusion via Cross-Modal Latent Synthesis and Attention Guided Restoration for Industrial Anomaly Detection](https://mlsanity.com/paper/2510.21793/) (2025)
- [Split-Fuse-Transport: Annotation-Free Saliency via Dual Clustering and Optimal Transport Alignment](https://mlsanity.com/paper/2510.17484/) (2025)
- [Component-Aware Sketch-to-Image Generation Using Self-Attention Encoding and Coordinate-Preserving Fusion](https://mlsanity.com/paper/2603.09484/) (2026)

## Abstract (arXiv)

This paper presents a novel deep-learning framework that significantly enhances the transformation of rudimentary face sketches into high-fidelity colour images. Employing a Convolutional Block Attention-based Auto-encoder Network (CA2N), our approach effectively captures and enhances critical facial features through a block attention mechanism within an encoder-decoder architecture. Subsequently, the framework utilises a noise-induced conditional Generative Adversarial Network (cGAN) process that allows the system to maintain high performance even on domains unseen during the training. These enhancements lead to considerable improvements in image realism and fidelity, with our model achieving superior performance metrics that outperform the best method by FID margin of 17, 23, and 38 on CelebAMask-HQ, CUHK, and CUFSF datasets; respectively. The model sets a new state-of-the-art in sketch-to-image generation, can generalize across sketch types, and offers a robust solution for applications such as criminal identification in law enforcement.