4 papers
Spatial Gram Alignment for Ultra-High-Resolution Image Synthesis
Jinjin Zhang, Xiefan Guo, Di Huang
Modern ultra-high-resolution image synthesis relies heavily on the robust generative capacity of large-scale pre-trained Latent Diffusion Models (LDMs). While recent representation…
What Makes Synthetic Data Effective in Image Segmentation
Jinjin Zhang, Xiefan Guo, Yizhou Jin +2
Driven by rapid advances in large-scale generative models, synthetic data has emerged as a promising solution for visual understanding. While modern diffusion models achieve remark…
Ultra-High-Resolution Image Synthesis: Data, Method and Evaluation
Jinjin Zhang, Qiuyu Huang, Junjie Liu +2
Ultra-high-resolution image synthesis holds significant potential, yet remains an underexplored challenge due to the absence of standardized benchmarks and computational constraint…
Diffusion-4K: Ultra-High-Resolution Image Synthesis with Latent Diffusion Models
Jinjin Zhang, Qiuyu Huang, Junjie Liu +2
In this paper, we present Diffusion-4K, a novel framework for direct ultra-high-resolution image synthesis using text-to-image diffusion models. The core advancements include: (1)…