Face Reenactment

24 papers with code • 0 benchmarks • 1 datasets

Face Reenactment is an emerging conditional face synthesis task that aims at fulfilling two goals simultaneously: 1) transfer a source face shape to a target face; while 2) preserve the appearance and the identity of the target face.

Source: One-shot Face Reenactment

Datasets


AniPortrait: Audio-Driven Synthesis of Photorealistic Portrait Animation

scutzzj/aniportrait 26 Mar 2024

In this study, we propose AniPortrait, a novel framework for generating high-quality animation driven by audio and a reference portrait image.

708
26 Mar 2024

Deepfake Generation and Detection: A Benchmark and Survey

flyingby/awesome-deepfake-generation-and-detection 26 Mar 2024

In addition to the advancements in deepfake generation, corresponding detection technologies need to continuously evolve to regulate the potential misuse of deepfakes, such as for privacy invasion and phishing attacks.

7
26 Mar 2024

BakedAvatar: Baking Neural Fields for Real-Time Head Avatar Synthesis

buaavrcg/BakedAvatar 9 Nov 2023

Synthesizing photorealistic 4D human head avatars from videos is essential for VR/AR, telepresence, and video game applications.

259
09 Nov 2023

HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces

stelabou/hyperreenact ICCV 2023

In this paper, we present our method for neural face reenactment, called HyperReenact, that aims to generate realistic talking head images of a source identity, driven by a target facial pose.

62
20 Jul 2023

ReliableSwap: Boosting General Face Swapping Via Reliable Supervision

ygtxr1997/reliableswap 8 Jun 2023

To avoid the potential artifacts and drive the distribution of the network output close to the natural one, we reversely take synthetic images as input while the real face as reliable supervision during the training stage of face swapping.

173
08 Jun 2023

StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single Video

lizhenwangt/styleavatar 1 May 2023

Results and experiments demonstrate the superiority of our method in terms of image quality, full portrait video generation, and real-time re-animation compared to existing facial reenactment methods.

340
01 May 2023

Compressing Video Calls using Synthetic Talking Heads

berlin0610/awesome-generative-face-video-coding 7 Oct 2022

We use a state-of-the-art face reenactment network to detect key points in the non-pivot frames and transmit them to the receiver.

13
07 Oct 2022

Audio-Visual Face Reenactment

mdv3101/AVFR-Gan 6 Oct 2022

The identity-aware generator takes the source image and the warped motion features as input to generate a high-quality output with fine-grained details.

153
06 Oct 2022

StyleMask: Disentangling the Style Space of StyleGAN2 for Neural Face Reenactment

stelabou/stylemask 27 Sep 2022

In this paper we address the problem of neural face reenactment, where, given a pair of a source and a target facial image, we need to transfer the target's pose (defined as the head pose and its facial expressions) to the source image, by preserving at the same time the source's identity characteristics (e. g., facial shape, hair style, etc), even in the challenging case where the source and the target faces belong to different identities.

103
27 Sep 2022

3DFaceShop: Explicitly Controllable 3D-Aware Portrait Generation

junshutang/3DFaceShop 12 Sep 2022

In contrast to the traditional avatar creation pipeline which is a costly process, contemporary generative approaches directly learn the data distribution from photographs.

204
12 Sep 2022