activity
20242026
collaborators

6 papers

cs.CV2026

FlashVideo: Flowing Fidelity to Detail for Efficient High-Resolution Video Generation

Shilong Zhang, Wenbo Li, Shoufa Chen +7

DiT models have achieved great success in text-to-video generation, leveraging their scalability in model capacity and data scale. High content and motion fidelity aligned with tex…

cs.CV2025

A Generative Foundation Model for Chest Radiography

Yuanfeng Ji, Dan Lin, Xiyue Wang +12

The scarcity of well-annotated diverse medical images is a major hurdle for developing reliable AI models in healthcare. Substantial technical advances have been made in generative…

cs.CV2025

PixelFlow: Pixel-Space Generative Models with Flow

Shoufa Chen, Chongjian Ge, Shilong Zhang +2

We present PixelFlow, a family of image generation models that operate directly in the raw pixel space, in contrast to the predominant latent-space models. This approach simplifies…

cs.CV2025

Goku: Flow Based Video Generative Foundation Models

Shoufa Chen, Chongjian Ge, Yuqi Zhang +19

This paper introduces Goku, a state-of-the-art family of joint image-and-video generation models leveraging rectified flow Transformers to achieve industry-leading performance. We…

cs.CV2024

Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM

Yatai Ji, Jiacheng Zhang, Jie Wu +9

Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality o…

cs.CV2024

CompGS: Unleashing 2D Compositionality for Compositional Text-to-3D via Dynamically Optimizing 3D Gaussians

Chongjian Ge, Chenfeng Xu, Yuanfeng Ji +6

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, gener…