As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated
strong power of learning complex structures and meaningful semantics. However, relying …

While generative models produce high-quality images of concepts learned from a large-
scale database, a user often wishes to synthesize instantiations of their own concepts (for …

Large-scale diffusion-based generative models have led to breakthroughs in text-
conditioned high-resolution image synthesis. Starting from random noise, such text-to-image …

As several industries are moving towards modeling massive 3D virtual worlds, the need for
content creation tools that can scale in terms of the quantity, quality, and diversity of 3D …

Large-scale text-to-image diffusion models can generate high-fidelity images with powerful
compositional ability. However, these models are typically trained on an enormous amount …

Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of
large-scale real-scanned 3D databases. To facilitate the development of 3D perception …

Recent large-scale generative models learned on big data are capable of synthesizing
incredible images yet suffer from limited controllability. This work offers a new generation …

Existing text-to-image diffusion models struggle to synthesize realistic images given dense
captions, where each text prompt provides a detailed description for a specific image region …

Text-to-Image models have introduced a remarkable leap in the evolution of machine
learning, demonstrating high-quality synthesis of images from a given text-prompt. However …