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20242026
most citedIMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models

1 citations · 3 across the 11 of their papers we have counts for

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cs.CV2025

Decoupled DMD: CFG Augmentation as the Spear, Distribution Matching as the Shield

Dongyang Liu, Peng Gao, David Liu +8

Diffusion model distillation has emerged as a powerful technique for creating efficient few-step and single-step generators. Among these, Distribution Matching Distillation (DMD) a…

cs.CV2025★ 1 cited

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,…

cs.CV2025

OneVAE: Joint Discrete and Continuous Optimization Helps Discrete Video VAE Train Better

Yupeng Zhou, Zhen Li, Ziheng Ouyang +8

Encoding videos into discrete tokens could align with text tokens to facilitate concise and unified multi-modal LLMs, yet introducing significant spatiotemporal compression compare…

cs.CV2025

VisualCloze: A Universal Image Generation Framework via Visual In-Context Learning

Zhong-Yu Li, Ruoyi Du, Juncheng Yan +6

Recent progress in diffusion models significantly advances various image generation tasks. However, the current mainstream approach remains focused on building task-specific models…

cs.CV2025

Lumina-Image 2.0: A Unified and Efficient Image Generative Framework

Qi Qin, Le Zhuo, Yi Xin +20

We introduce Lumina-Image 2.0, an advanced text-to-image generation framework that achieves significant progress compared to previous work, Lumina-Next. Lumina-Image 2.0 is built u…

cs.CV2025★ 1 cited

IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models

Jiayi Lei, Renrui Zhang, Xiangfei Hu +12

With the rapid development of diffusion models, text-to-image(T2I) models have made significant progress, showcasing impressive abilities in prompt following and image generation.…