Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Deep reinforcement learning (RL) has become one of the most popular topics in artificial
intelligence research. It has been widely used in various fields, such as end-to-end control …

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 …

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 …

Denoising diffusion probabilistic models are a promising new class of generative models
that mark a milestone in high-quality image generation. This paper showcases their ability to …

Intelligent agents need to generalize from past experience to achieve goals in complex
environments. World models facilitate such generalization and allow learning behaviors …

We present VideoGPT: a conceptually simple architecture for scaling likelihood based
generative modeling to natural videos. VideoGPT uses VQ-VAE that learns downsampled …

The predictive learning of spatiotemporal sequences aims to generate future images by
learning from the historical context, where the visual dynamics are believed to have modular …