The recent wave of AI-generated content (AIGC) has witnessed substantial success in
computer vision, with the diffusion model playing a crucial role in this achievement. Due to …

Advancements in machine learning have recently enabled the hyper-realistic synthesis of
prose, images, audio and video data, in what is referred to as artificial intelligence (AI) …

Animating a still image offers an engaging visual experience. Traditional image animation
techniques mainly focus on animating natural scenes with stochastic dynamics (eg clouds …

A diffusion probabilistic model (DPM), which constructs a forward diffusion process by
gradually adding noise to data points and learns the reverse denoising process to generate …

Conditional image-to-video (cI2V) generation aims to synthesize a new plausible video
starting from an image (eg, a person's face) and a condition (eg, an action class label like …

Generating talking head videos through a face image and a piece of speech audio still
contains many challenges. ie, unnatural head movement, distorted expression, and identity …

In this study, we introduce a methodology for human image animation by leveraging a 3D
human parametric model within a latent diffusion framework to enhance shape alignment …

Character Animation aims to generating character videos from still images through driving
signals. Currently diffusion models have become the mainstream in visual generation …

3D avatar creation plays a crucial role in the digital age. However, the whole production
process is prohibitively time-consuming and labor-intensive. To democratize this technology …

We present an approach to modeling an image-space prior on scene motion. Our prior is
learned from a collection of motion trajectories extracted from real video sequences …