37 citations · 64 across the 10 of their papers we have counts for
4 papers · 1 filter
Enhancing Detail Preservation for Customized Text-to-Image Generation: A Regularization-Free Approach
Yufan Zhou, Ruiyi Zhang, Tong Sun +1
Recent text-to-image generation models have demonstrated impressive capability of generating text-aligned images with high fidelity. However, generating images of novel concept pro…
Shifted Diffusion for Text-to-image Generation
Yufan Zhou, Bingchen Liu, Yizhe Zhu +3
We present Corgi, a novel method for text-to-image generation. Corgi is based on our proposed shifted diffusion model, which achieves better image embedding generation from input t…
Lafite2: Few-shot Text-to-Image Generation
Yufan Zhou, Chunyuan Li, Changyou Chen +2
Text-to-image generation models have progressed considerably in recent years, which can now generate impressive realistic images from arbitrary text. Most of such models are traine…
LAFITE: Towards Language-Free Training for Text-to-Image Generation
Yufan Zhou, Ruiyi Zhang, Changyou Chen +6
One of the major challenges in training text-to-image generation models is the need of a large number of high-quality image-text pairs. While image samples are often easily accessi…