# Head2Head++: Deep Facial Attributes Re-Targeting

arXiv: https://arxiv.org/abs/2006.10199 · HTML: https://mlsanity.com/paper/2006.10199/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Jun 2020.

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

- [RigNeRF: Fully Controllable Neural 3D Portraits](https://mlsanity.com/paper/2206.06481/) (2022)
- [SMIRK: 3D Facial Expressions through Analysis-by-Neural-Synthesis](https://mlsanity.com/paper/2404.04104/) (2024)
- [AvatarMAV: Fast 3D Head Avatar Reconstruction Using Motion-Aware Neural Voxels](https://mlsanity.com/paper/2211.13206/) (2022)
- [StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single Video](https://mlsanity.com/paper/2305.00942/) (2023)
- [LatentAvatar: Learning Latent Expression Code for Expressive Neural Head Avatar](https://mlsanity.com/paper/2305.01190/) (2023)
- [DPE: Disentanglement of Pose and Expression for General Video Portrait Editing](https://mlsanity.com/paper/2301.06281/) (2023)
- [HAvatar: High-fidelity Head Avatar via Facial Model Conditioned Neural Radiance Field](https://mlsanity.com/paper/2309.17128/) (2023)
- [FLAME-in-NeRF : Neural control of Radiance Fields for Free View Face Animation](https://mlsanity.com/paper/2108.04913/) (2021)
- [Neural Emotion Director: Speech-preserving semantic control of facial expressions in "in-the-wild" videos](https://mlsanity.com/paper/2112.00585/) (2021)
- [Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis](https://mlsanity.com/paper/2109.02081/) (2021)
- [Tri2-plane: Thinking Head Avatar via Feature Pyramid](https://mlsanity.com/paper/2401.09386/) (2024)
- [3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views](https://mlsanity.com/paper/2212.02997/) (2022)
- [Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control](https://mlsanity.com/paper/2208.02210/) (2022)
- [Efficient 3D Implicit Head Avatar with Mesh-anchored Hash Table Blendshapes](https://mlsanity.com/paper/2404.01543/) (2024)
- [Contrastive Decoupled Representation Learning and Regularization for Speech-Preserving Facial Expression Manipulation](https://mlsanity.com/paper/2504.05672/) (2025)
- [Deep Semantic Manipulation of Facial Videos](https://mlsanity.com/paper/2111.07902/) (2021)
- [Exploiting Temporal Audio-Visual Correlation Embedding for Audio-Driven One-Shot Talking Head Animation](https://mlsanity.com/paper/2504.05746/) (2025)
- [MyPortrait: Morphable Prior-Guided Personalized Portrait Generation](https://mlsanity.com/paper/2312.02703/) (2023)
- [Neural Text to Articulate Talk: Deep Text to Audiovisual Speech Synthesis achieving both Auditory and Photo-realism](https://mlsanity.com/paper/2312.06613/) (2023)
- [JEAN: Joint Expression and Audio-guided NeRF-based Talking Face Generation](https://mlsanity.com/paper/2409.12156/) (2024)
- [Learning Spatial-Temporal Coherent Correlations for Speech-Preserving Facial Expression Manipulation](https://mlsanity.com/paper/2604.20226/) (2026)
- [Neural Sign Reenactor: Deep Photorealistic Sign Language Retargeting](https://mlsanity.com/paper/2209.01470/) (2022)
- [CP-EB: Talking Face Generation with Controllable Pose and Eye Blinking Embedding](https://mlsanity.com/paper/2311.08673/) (2023)
- [Head2HeadFS: Video-based Head Reenactment with Few-shot Learning](https://mlsanity.com/paper/2103.16229/) (2021)
- [Dynamic Neural Portraits](https://mlsanity.com/paper/2211.13994/) (2022)
- [Controllable One-Shot Face Video Synthesis With Semantic Aware Prior](https://mlsanity.com/paper/2304.14471/) (2023)
- [Solutions to Deepfakes: Can Camera Hardware, Cryptography, and Deep Learning Verify Real Images?](https://mlsanity.com/paper/2407.04169/) (2024)
- [Electromyography-Informed Facial Expression Reconstruction for Physiological-Based Synthesis and Analysis](https://mlsanity.com/paper/2503.09556/) (2025)
- [Controllable Dynamic Appearance for Neural 3D Portraits](https://mlsanity.com/paper/2309.11009/) (2023)
- [Exploring Talking Head Models With Adjacent Frame Prior for Speech-Preserving Facial Expression Manipulation](https://mlsanity.com/paper/2601.12876/) (2026)

## Abstract (arXiv)

Facial video re-targeting is a challenging problem aiming to modify the facial attributes of a target subject in a seamless manner by a driving monocular sequence. We leverage the 3D geometry of faces and Generative Adversarial Networks (GANs) to design a novel deep learning architecture for the task of facial and head reenactment. Our method is different to purely 3D model-based approaches, or recent image-based methods that use Deep Convolutional Neural Networks (DCNNs) to generate individual frames. We manage to capture the complex non-rigid facial motion from the driving monocular performances and synthesise temporally consistent videos, with the aid of a sequential Generator and an ad-hoc Dynamics Discriminator network. We conduct a comprehensive set of quantitative and qualitative tests and demonstrate experimentally that our proposed method can successfully transfer facial expressions, head pose and eye gaze from a source video to a target subject, in a photo-realistic and faithful fashion, better than other state-of-the-art methods. Most importantly, our system performs end-to-end reenactment in nearly real-time speed (18 fps).