8 citations · 14 across the 5 of their papers we have counts for
5 papers · 1 filter
DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning
Yuxuan Duan, Yan Hong, Bo Zhang +6
The recent progress in text-to-image models pretrained on large-scale datasets has enabled us to generate various images as long as we provide a text prompt describing what we want…
Dataset Distillation in Latent Space
Yuxuan Duan, Jianfu Zhang, Liqing Zhang
Dataset distillation (DD) is a newly emerging research area aiming at alleviating the heavy computational load in training models on large datasets. It tries to distill a large dat…
ControlCom: Controllable Image Composition using Diffusion Model
Bo Zhang, Yuxuan Duan, Jun Lan +4
Image composition targets at synthesizing a realistic composite image from a pair of foreground and background images. Recently, generative composition methods are built on large p…
WeditGAN: Few-Shot Image Generation via Latent Space Relocation
Yuxuan Duan, Li Niu, Yan Hong +1
In few-shot image generation, directly training GAN models on just a handful of images faces the risk of overfitting. A popular solution is to transfer the models pretrained on lar…
Few-Shot Defect Image Generation via Defect-Aware Feature Manipulation
Yuxuan Duan, Yan Hong, Li Niu +1
The performances of defect inspection have been severely hindered by insufficient defect images in industries, which can be alleviated by generating more samples as data augmentati…