We introduce Motion-I2V, a novel framework for consistent and controllable text-guided
image-to-video generation (I2V). In contrast to previous methods that directly learn the …

Image-to-video (I2V) generation aims to use the initial frame (alongside a text prompt) to
create a video sequence. A grand challenge in I2V generation is to maintain visual …

The field of portrait image animation, driven by speech audio input, has experienced
significant advancements in the generation of realistic and dynamic portraits. This research …

Clipart, a pre-made graphic art form, offers a convenient and efficient way of illustrating
visual content. Traditional workflows to convert static clipart images into motion sequences …

Video generation has witnessed significant advancements, yet evaluating these models
remains a challenge. A comprehensive evaluation benchmark for video generation is …

We introduce MarDini, a new family of video diffusion models that integrate the advantages
of masked auto-regression (MAR) into a unified diffusion model (DM) framework. Here, MAR …

Foley is a term commonly used in filmmaking, referring to the addition of daily sound effects
to silent films or videos to enhance the auditory experience. Video-to-Audio (V2A), as a …

Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in
creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V) …

Recently, video generation has achieved significant rapid development based on superior
text-to-image generation techniques. In this work, we propose a high fidelity framework for …

This study aims to achieve more precise and versatile object control in image-to-video (I2V)
generation. Current methods typically represent the spatial movement of target objects with …