1 citations · 1 across the 2 of their papers we have counts for
6 papers
Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer
Image Team, Huanqia Cai, Sihan Cao +21
The landscape of high-performance image generation models is currently dominated by proprietary systems, such as Nano Banana Pro and Seedream 4.0. Leading open-source alternatives,…
High-Fidelity Two-Step Image Generation via Teacher-Aligned End-to-End Distillation
Dongyang Liu, Ruoyi Du, David Liu +7
Few-step diffusion distillation has become increasingly mature for 4-8-step generation, yet pushing further to 2 steps remains challenging. In this work, we introduce Z-Image Turbo…
Joint Deblurring and 3D Reconstruction for Macrophotography
Yifan Zhao, Liangchen Li, Yuqi Zhou +3
Macro lens has the advantages of high resolution and large magnification, and 3D modeling of small and detailed objects can provide richer information. However, defocus blur in mac…
Shape from Semantics: 3D Shape Generation from Multi-View Semantics
Liangchen Li, Caoliwen Wang, Yuqi Zhou +2
Existing 3D reconstruction methods utilize guidances such as 2D images, 3D point clouds, shape contours and single semantics to recover the 3D surface, which limits the creative ex…
MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost
Sen Xing, Muyan Zhong, Zeqiang Lai +5
In this work, we explore a cost-effective framework for multilingual image generation. We find that, unlike models tuned on high-quality images with multilingual annotations, lever…
Bidirectional Consistency Models
Liangchen Li, Jiajun He
Diffusion models (DMs) are capable of generating remarkably high-quality samples by iteratively denoising a random vector, a process that corresponds to moving along the probabilit…