7 papers · 1 filter
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…
Lumina-mGPT 2.0: Stand-Alone AutoRegressive Image Modeling
Yi Xin, Juncheng Yan, Qi Qin +18
We present Lumina-mGPT 2.0, a stand-alone, decoder-only autoregressive model that revisits and revitalizes the autoregressive paradigm for high-quality image generation and beyond.…
OmniCaptioner: One Captioner to Rule Them All
Yiting Lu, Jiakang Yuan, Zhen Li +17
We propose OmniCaptioner, a versatile visual captioning framework for generating fine-grained textual descriptions across a wide variety of visual domains. Unlike prior methods lim…
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…
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…
Lumina-Video: Efficient and Flexible Video Generation with Multi-scale Next-DiT
Dongyang Liu, Shicheng Li, Yutong Liu +16
Recent advancements have established Diffusion Transformers (DiTs) as a dominant framework in generative modeling. Building on this success, Lumina-Next achieves exceptional perfor…