14 citations · 43 across the 8 of their papers we have counts for
8 papers
ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models
Jingyuan Zhu, Shiyu Li, Yuxuan Liu +4
Modern diffusion-based image generative models have made significant progress and become promising to enrich training data for the object detection task. However, the generation qu…
Isolated Diffusion: Optimizing Multi-Concept Text-to-Image Generation Training-Freely with Isolated Diffusion Guidance
Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1
Large-scale text-to-image diffusion models have achieved great success in synthesizing high-quality and diverse images given target text prompts. Despite the revolutionary image ge…
DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data
Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1
Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Typic…
Few-shot 3D Shape Generation
Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1
Realistic and diverse 3D shape generation is helpful for a wide variety of applications such as virtual reality, gaming, and animation. Modern generative models, such as GANs and d…
Prediction with Incomplete Data under Agnostic Mask Distribution Shift
Yichen Zhu, Jian Yuan, Bo Jiang +4
Data with missing values is ubiquitous in many applications. Recent years have witnessed increasing attention on prediction with only incomplete data consisting of observed feature…
MotionVideoGAN: A Novel Video Generator Based on the Motion Space Learned from Image Pairs
Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1
Video generation has achieved rapid progress benefiting from high-quality renderings provided by powerful image generators. We regard the video synthesis task as generating a seque…
Few-shot Image Generation with Diffusion Models
Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1
Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Howev…
Few-shot Image Generation via Masked Discrimination
Jingyuan Zhu, Huimin Ma, Jiansheng Chen +1
Few-shot image generation aims to generate images of high quality and great diversity with limited data. However, it is difficult for modern GANs to avoid overfitting when trained…