most citedLumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

2 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2025

Resurrect Mask AutoRegressive Modeling for Efficient and Scalable Image Generation

Yi Xin, Le Zhuo, Qi Qin +8

AutoRegressive (AR) models have made notable progress in image generation, with Masked AutoRegressive (MAR) models gaining attention for their efficient parallel decoding. However,…

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

LeX-Art: Rethinking Text Generation via Scalable High-Quality Data Synthesis

Shitian Zhao, Qilong Wu, Xinyue Li +10

We introduce LeX-Art, a comprehensive suite for high-quality text-image synthesis that systematically bridges the gap between prompt expressiveness and text rendering fidelity. Our…

cs.CV2025

TIDE : Temporal-Aware Sparse Autoencoders for Interpretable Diffusion Transformers in Image Generation

Victor Shea-Jay Huang, Le Zhuo, Yi Xin +6

Diffusion Transformers (DiTs) are a powerful yet underexplored class of generative models compared to U-Net-based diffusion architectures. We propose TIDE-Temporal-aware sparse aut…

cs.CV2024

I-Max: Maximize the Resolution Potential of Pre-trained Rectified Flow Transformers with Projected Flow

Ruoyi Du, Dongyang Liu, Le Zhuo +4

Rectified Flow Transformers (RFTs) offer superior training and inference efficiency, making them likely the most viable direction for scaling up diffusion models. However, progress…

cs.CV2024

Customize Your Visual Autoregressive Recipe with Set Autoregressive Modeling

Wenze Liu, Le Zhuo, Yi Xin +3

We introduce a new paradigm for AutoRegressive (AR) image generation, termed Set AutoRegressive Modeling (SAR). SAR generalizes the conventional AR to the next-set setting, i.e., s…

cs.CV2024

PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions

Weifeng Lin, Xinyu Wei, Renrui Zhang +8

This paper presents a versatile image-to-image visual assistant, PixWizard, designed for image generation, manipulation, and translation based on free-from language instructions. T…

cs.CV2024★ 2 cited

Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining

Dongyang Liu, Shitian Zhao, Le Zhuo +7

We present Lumina-mGPT, a family of multimodal autoregressive models capable of various vision and language tasks, particularly excelling in generating flexible photorealistic imag…

cs.CV2024

VEnhancer: Generative Space-Time Enhancement for Video Generation

Jingwen He, Tianfan Xue, Dongyang Liu +6

We present VEnhancer, a generative space-time enhancement framework that improves the existing text-to-video results by adding more details in spatial domain and synthetic detailed…