62 citations · 116 across the 20 of their papers we have counts for
9 papers · 1 filter
Infinite-ID: Identity-preserved Personalization via ID-semantics Decoupling Paradigm
Yi Wu, Ziqiang Li, Heliang Zheng +2
Drawing on recent advancements in diffusion models for text-to-image generation, identity-preserved personalization has made significant progress in accurately capturing specific i…
Peer is Your Pillar: A Data-unbalanced Conditional GANs for Few-shot Image Generation
Ziqiang Li, Chaoyue Wang, Xue Rui +3
Few-shot image generation aims to train generative models using a small number of training images. When there are few images available for training (e.g. 10 images), Learning From…
Domain Re-Modulation for Few-Shot Generative Domain Adaptation
Yi Wu, Ziqiang Li, Chaoyue Wang +4
In this study, we delve into the task of few-shot Generative Domain Adaptation (GDA), which involves transferring a pre-trained generator from one domain to a new domain using only…
FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs
Ziqiang Li, Chaoyue Wang, Heliang Zheng +2
Data-Efficient GANs (DE-GANs), which aim to learn generative models with a limited amount of training data, encounter several challenges for generating high-quality samples. Since…
Data-Efficient Backdoor Attacks
Pengfei Xia, Ziqiang Li, Wei Zhang +1
Recent studies have proven that deep neural networks are vulnerable to backdoor attacks. Specifically, by mixing a small number of poisoned samples into the training set, the behav…
A Comprehensive Survey on Data-Efficient GANs in Image Generation
Ziqiang Li, Beihao Xia, Jing Zhang +2
Generative Adversarial Networks (GANs) have achieved remarkable achievements in image synthesis. These successes of GANs rely on large scale datasets, requiring too much cost. With…
Exploring The Effect of High-frequency Components in GANs Training
Ziqiang Li, Pengfei Xia, Xue Rui +1
Generative Adversarial Networks (GANs) have the ability to generate images that are visually indistinguishable from real images. However, recent studies have revealed that generate…
Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation
Ziqiang Li, Rentuo Tao, Hongjing Niu +1
Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution and drug discovery, etc., by now, the inner pro…
DA-RefineNet:A Dual Input Whole Slide Image Segmentation Algorithm Based on Attention
Ziqiang Li, Rentuo Tao, Qianrun Wu +1
Automatic medical image segmentation has wide applications for disease diagnosing. However, it is much more challenging than natural optical image segmentation due to the high-reso…