The pursuit of controllability as a higher standard of visual content creation has yielded
remarkable progress in customizable image synthesis. However, achieving controllable …

This presentation introduces a self-supervised learning approach to the synthesis of new
videos clips from old ones, with several new key elements for improved spatial resolution …

Most methods for conditional video synthesis use a single modality as the condition. This
comes with major limitations. For example, it is problematic for a model conditioned on an …

Video generation remains a challenging task due to spatiotemporal complexity and the
requirement of synthesizing diverse motions with temporal consistency. Previous works …

Creating high-dynamic videos such as motion-rich actions and sophisticated visual effects
poses a significant challenge in the field of artificial intelligence. Unfortunately current state …

Most existing video diffusion models (VDMs) are limited to mere text conditions. Thereby,
they are usually lacking in control over visual appearance and geometry structure of the …

We present a self-supervised approach with pose perceptual loss for automatic dance video
generation. Our method can produce a realistic dance video that conforms to the beats and …

We study the problem of video-to-video synthesis, whose goal is to learn a mapping function
from an input source video (eg, a sequence of semantic segmentation masks) to an output …

Recent text-to-video diffusion models have achieved impressive progress. In practice, users
often desire the ability to control object motion and camera movement independently for …

Generating controllable videos conforming to user intentions is an appealing yet challenging
topic in computer vision. To enable maneuverable control in line with user intentions, a …