activity
20242026
most citedQwen-Image Technical Report

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation

Niantong Li, Guangzheng Hu, Weixu Qiao +35

Text-to-Image generation has evolved from basic image synthesis into a frequently used core capability in professional creative workflows, where simple text-image alignment can no…

cs.CV2026

Qwen-Image-VAE-2.0 Technical Report

Zekai Zhang, Deqing Li, Kuan Cao +27

We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…

cs.CV2026

Qwen-Image-2.0 Technical Report

Bing Zhao, Chenfei Wu, Deqing Li +72

We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…

cs.CV2025

Qwen-Image-Layered: Towards Inherent Editability via Layer Decomposition

Shengming Yin, Zekai Zhang, Zecheng Tang +11

Recent visual generative models often struggle with consistency during image editing due to the entangled nature of raster images, where all visual content is fused into a single c…

cs.CV2025★ 2 cited

Qwen-Image Technical Report

Chenfei Wu, Jiahao Li, Jingren Zhou +36

We present Qwen-Image, an image generation foundation model in the Qwen series that achieves significant advances in complex text rendering and precise image editing. To address th…

cs.CV2024★ 1 cited

EG4D: Explicit Generation of 4D Object without Score Distillation

Qi Sun, Zhiyang Guo, Ziyu Wan +5

In recent years, the increasing demand for dynamic 3D assets in design and gaming applications has given rise to powerful generative pipelines capable of synthesizing high-quality…