Recent advances in text-to-image generation have made remarkable progress in
synthesizing realistic human photos conditioned on given text prompts. However existing …

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 …

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 …

Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using
supervision from pre-trained text-to-video models. However, existing representations for …

Controllability plays a crucial role in video generation since it allows users to create desired
content. However, existing models largely overlooked the precise control of camera pose …

Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to
collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a …

Generating rich and controllable motion is a pivotal challenge in video synthesis. We
propose Boximator, a new approach for fine-grained motion control. Boximator introduces …

We introduce DragAPart, a method that, given an image and a set of drags as input, can
generate a new image of the same object in a new state, compatible with the action of the …

World models can foresee the outcomes of different actions, which is of paramount
importance for autonomous driving. Nevertheless, existing driving world models still have …

Filmmaking and animation production often require sophisticated techniques for
coordinating camera transitions and object movements, typically involving labor-intensive …