The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

In a world with rapidly growing levels of automation, robotics is playing an increasingly
significant role in every aspect of human endeavour. In particular, many types of mobile …

Abstract Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding
excessive compute demands by training a diffusion model in a compressed lower …

We present Phenaki, a model capable of realistic video synthesis given a sequence of
textual prompts. Generating videos from text is particularly challenging due to the …

Generating temporally coherent high fidelity video is an important milestone in generative
modeling research. We make progress towards this milestone by proposing a diffusion …

Video prediction is a challenging task. The quality of video frames from current state-of-the-
art (SOTA) generative models tends to be poor and generalization beyond the training data …

Abstract We introduce the MAsked Generative VIdeo Transformer, MAGVIT, to tackle various
video synthesis tasks with a single model. We introduce a 3D tokenizer to quantize a video …

Abstract From CNN, RNN, to ViT, we have witnessed remarkable advancements in video
prediction, incorporating auxiliary inputs, elaborate neural architectures, and sophisticated …

This paper presents a unified multimodal pre-trained model called NÜWA that can generate
new or manipulate existing visual data (ie, images and videos) for various visual synthesis …

The recent wave of AI-generated content has witnessed the great development and success
of Text-to-Image (T2I) technologies. By contrast Text-to-Video (T2V) still falls short of …