This paper presents ER-NeRF, a novel conditional Neural Radiance Fields (NeRF) based
architecture for talking portrait synthesis that can concurrently achieve fast convergence, real …

Diffusion models have shown remarkable success in a variety of downstream generative
tasks, yet remain under-explored in the important and challenging expressive talking head …

Abstract We propose DiffSHEG a Diffusion-based approach for Speech-driven Holistic 3D
Expression and Gesture generation. While previous works focused on co-speech gesture or …

In this paper we abstract the process of people hearing speech extracting meaningful cues
and creating various dynamically audio-consistent talking faces termed Listening and …

Abstract" Generalizability" is seen as the hallmark quality of a good deepfake detection
model. However, standard out-of-domain evaluation datasets are very similar in form to the …

Audio-driven portrait animation aims to synthesize portrait videos that are conditioned by
given audio. Animating high-fidelity and multimodal video portraits has a variety of …

Our goal with this survey is to provide an overview of the state of the art deep learning
methods for face generation and editing using StyleGAN. The survey covers the evolution of …

Multimodal-driven talking face generation refers to animating a portrait with the given pose,
expression, and gaze transferred from the driving image and video, or estimated from the …

We aim to edit the lip movements in talking video according to the given speech while
preserving the personal identity and visual details. The task can be decomposed into two …

Predominant techniques on talking head generation largely depend on 2D information,
including facial appearances and motions from input face images. Nevertheless, dense 3D …