# Cascade EF-GAN: Progressive Facial Expression Editing with Local Focuses

arXiv: https://arxiv.org/abs/2003.05905 · HTML: https://mlsanity.com/paper/2003.05905/

## Key facts

- Cited by 43 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Mar 2020.

## Built on by (most cited first, 30 of 43)

- [EditGAN: High-Precision Semantic Image Editing](https://mlsanity.com/paper/2111.03186/) (2021)
- [Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection](https://mlsanity.com/paper/2103.09096/) (2021)
- [MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion](https://mlsanity.com/paper/2311.12052/) (2023)
- [Diverse Image Inpainting with Bidirectional and Autoregressive Transformers](https://mlsanity.com/paper/2104.12335/) (2021)
- [Defect-GAN: High-Fidelity Defect Synthesis for Automated Defect Inspection](https://mlsanity.com/paper/2103.15158/) (2021)
- [WaveFill: A Wavelet-based Generation Network for Image Inpainting](https://mlsanity.com/paper/2107.11027/) (2021)
- [Unbalanced Feature Transport for Exemplar-based Image Translation](https://mlsanity.com/paper/2106.10482/) (2021)
- [Blind Image Super-Resolution via Contrastive Representation Learning](https://mlsanity.com/paper/2107.00708/) (2021)
- [ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training](https://mlsanity.com/paper/2110.05323/) (2021)
- [Modulated Contrast for Versatile Image Synthesis](https://mlsanity.com/paper/2203.09333/) (2022)
- [Bi-level Feature Alignment for Versatile Image Translation and Manipulation](https://mlsanity.com/paper/2107.03021/) (2021)
- [Towards Counterfactual Image Manipulation via CLIP](https://mlsanity.com/paper/2207.02812/) (2022)
- [GenCo: Generative Co-training for Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2110.01254/) (2021)
- [Discrete Point-wise Attack Is Not Enough: Generalized Manifold Adversarial Attack for Face Recognition](https://mlsanity.com/paper/2301.06083/) (2022)
- [ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees](https://mlsanity.com/paper/2304.08928/) (2023)
- [MOGAN: Morphologic-structure-aware Generative Learning from a Single Image](https://mlsanity.com/paper/2103.02997/) (2021)
- [FRIH: Fine-grained Region-aware Image Harmonization](https://mlsanity.com/paper/2205.06448/) (2022)
- [Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation](https://mlsanity.com/paper/2106.06056/) (2021)
- [POCE: Pose-Controllable Expression Editing](https://mlsanity.com/paper/2304.08938/) (2023)
- [Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion](https://mlsanity.com/paper/2207.14172/) (2022)
- [EvoGAN: An Evolutionary Computation Assisted GAN](https://mlsanity.com/paper/2110.11583/) (2021)
- [Normal-guided Garment UV Prediction for Human Re-texturing](https://mlsanity.com/paper/2303.06504/) (2023)
- [US-GAN: On the importance of Ultimate Skip Connection for Facial Expression Synthesis](https://mlsanity.com/paper/2112.13002/) (2021)
- [Facial Expression Video Generation Based-On Spatio-temporal Convolutional GAN: FEV-GAN](https://mlsanity.com/paper/2210.11182/) (2022)
- [SeCGAN: Parallel Conditional Generative Adversarial Networks for Face Editing via Semantic Consistency](https://mlsanity.com/paper/2111.09298/) (2021)
- [Adaptively Enhancing Facial Expression Crucial Regions via Local Non-Local Joint Network](https://mlsanity.com/paper/2203.14045/) (2022)
- [Talking Head Generation Driven by Speech-Related Facial Action Units and Audio- Based on Multimodal Representation Fusion](https://mlsanity.com/paper/2204.12756/) (2022)
- [A comprehensive survey on semantic facial attribute editing using generative adversarial networks](https://mlsanity.com/paper/2205.10587/) (2022)
- [SARGAN: Spatial Attention-based Residuals for Facial Expression Manipulation](https://mlsanity.com/paper/2303.17212/) (2023)
- [FBC-GAN: Diverse and Flexible Image Synthesis via Foreground-Background Composition](https://mlsanity.com/paper/2107.03166/) (2021)

## Abstract (arXiv)

Recent advances in Generative Adversarial Nets (GANs) have shown remarkable improvements for facial expression editing. However, current methods are still prone to generate artifacts and blurs around expression-intensive regions, and often introduce undesired overlapping artifacts while handling large-gap expression transformations such as transformation from furious to laughing. To address these limitations, we propose Cascade Expression Focal GAN (Cascade EF-GAN), a novel network that performs progressive facial expression editing with local expression focuses. The introduction of the local focus enables the Cascade EF-GAN to better preserve identity-related features and details around eyes, noses and mouths, which further helps reduce artifacts and blurs within the generated facial images. In addition, an innovative cascade transformation strategy is designed by dividing a large facial expression transformation into multiple small ones in cascade, which helps suppress overlapping artifacts and produce more realistic editing while dealing with large-gap expression transformations. Extensive experiments over two publicly available facial expression datasets show that our proposed Cascade EF-GAN achieves superior performance for facial expression editing.