mlsanityData to 7 Oct 2026

One-shot Face Reenactment Using Appearance Adaptive Normalization

arXiv 2102.03984 ↗First posted 8 Feb 2021cs.CVcited by 12

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Abstract (arXiv)

The paper proposes a novel generative adversarial network for one-shot face reenactment, which can animate a single face image to a different pose-and-expression (provided by a driving image) while keeping its original appearance. The core of our network is a novel mechanism called appearance adaptive normalization, which can effectively integrate the appearance information from the input image into our face generator by modulating the feature maps of the generator using the learned adaptive parameters. Furthermore, we specially design a local net to reenact the local facial components (i.e., eyes, nose and mouth) first, which is a much easier task for the network to learn and can in turn provide explicit anchors to guide our face generator to learn the global appearance and pose-and-expression. Extensive quantitative and qualitative experiments demonstrate the significant efficacy of our model compared with prior one-shot methods.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 28 of its 40 references that are in the map. First posted on arXiv 8 Feb 2021.

Builds on

28 of 40 references.

References · 28

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  4. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  5. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  6. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  7. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
  8. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
  9. 2018Spectral Normalization for Generative Adversarial Networkscited by 1,618
  10. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,295
  11. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,199
  12. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
16 more
  1. 2019FaceForensics++: Learning to Detect Manipulated Facial Imagescited by 1,095
  2. 2018Self-Attention Generative Adversarial Networkscited by 809
  3. 2020First Order Motion Model for Image Animationcited by 698
  4. 2020Face2Face: Real-time Face Capture and Reenactment of RGB Videoscited by 631
  5. 2019Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensicscited by 573
  6. 2019FSGAN: Subject Agnostic Face Swapping and Reenactmentcited by 319
  7. 2019Few-Shot Adversarial Learning of Realistic Neural Talking Head Modelscited by 284
  8. 2018Deep Video Portraitscited by 265
  9. 2018Animating Arbitrary Objects via Deep Motion Transfercited by 206
  10. 2018X2Face: A network for controlling face generation by using images, audio, and pose codescited by 189
  11. 2017Modulating early visual processing by languagecited by 167
  12. 2018GANimation: Anatomically-aware Facial Animation from a Single Imagecited by 160
  13. 2019MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targetscited by 90
  14. 2018ReenactGAN: Learning to Reenact Faces via Boundary Transfercited by 85
  15. 2020Mesh Guided One-shot Face Reenactment using Graph Convolutional Networkscited by 30
  16. 2019One-shot Face Reenactmentcited by 21

Built on by

Cited by year

Citing papers per year: 2022: 7; 2023: 4; 2024: 1.

12 papers.

  1. 2022Progressive Disentangled Representation Learning for Fine-Grained Controllable Talking Head Synthesiscited by 93
  2. 2023DPE: Disentanglement of Pose and Expression for General Video Portrait Editingcited by 45
  3. 2023High-Fidelity and Freely Controllable Talking Head Video Generationcited by 42
  4. 2022Structure-Aware Motion Transfer with Deformable Anchor Modelcited by 34
  5. 2024Standing on the Shoulders of Giants: Reprogramming Visual-Language Model for General Deepfake Detectioncited by 30
  6. 2022Motion Transformer for Unsupervised Image Animationcited by 8
  7. 2023Learning Motion Refinement for Unsupervised Face Animationcited by 7
  8. 2023MaskRenderer: 3D-Infused Multi-Mask Realistic Face Reenactmentcited by 3
  9. 2022Fighting Malicious Media Data: A Survey on Tampering Detection and Deepfake Detectioncited by 2
  10. 2022Facial Action Units Detection Aided by Global-Local Expression Embeddingcited by 1
  11. 2022Semantic-aware One-shot Face Re-enactment with Dense Correspondence Estimationcited by 1
  12. 2022Global-to-local Expression-aware Embeddings for Facial Action Unit Detectioncited by 0