106 citations · 167 across the 10 of their papers we have counts for
10 papers
OSI: One-step Inversion Excels in Extracting Diffusion Watermarks
Yuwei Chen, Zhenliang He, Jia Tang +2
Watermarking is an important mechanism for provenance and copyright protection of diffusion-generated images. Training-free methods, exemplified by Gaussian Shading, embed watermar…
JoPano: Unified Panorama Generation via Joint Modeling
Wancheng Feng, Chen An, Zhenliang He +3
Panorama generation has recently attracted growing interest in the research community, with two core tasks, text-to-panorama and view-to-panorama generation. However, existing meth…
Jodi: Unification of Visual Generation and Understanding via Joint Modeling
Yifeng Xu, Zhenliang He, Meina Kan +2
Visual generation and understanding are two deeply interconnected aspects of human intelligence, yet they have been traditionally treated as separate tasks in machine learning. In…
CtrLoRA: An Extensible and Efficient Framework for Controllable Image Generation
Yifeng Xu, Zhenliang He, Shiguang Shan +1
Recently, large-scale diffusion models have made impressive progress in text-to-image (T2I) generation. To further equip these T2I models with fine-grained spatial control, approac…
StylizedGS: Controllable Stylization for 3D Gaussian Splatting
Dingxi Zhang, Yu-Jie Yuan, Zhuoxun Chen +4
As XR technology continues to advance rapidly, 3D generation and editing are increasingly crucial. Among these, stylization plays a key role in enhancing the appearance of 3D model…
Multimodal deep representation learning for quantum cross-platform verification
Yang Qian, Yuxuan Du, Zhenliang He +2
Cross-platform verification, a critical undertaking in the realm of early-stage quantum computing, endeavors to characterize the similarity of two imperfect quantum devices executi…
EigenGAN: Layer-Wise Eigen-Learning for GANs
Zhenliang He, Meina Kan, Shiguang Shan
Recent studies on Generative Adversarial Network (GAN) reveal that different layers of a generative CNN hold different semantics of the synthesized images. However, few GAN models…
PA-GAN: Progressive Attention Generative Adversarial Network for Facial Attribute Editing
Zhenliang He, Meina Kan, Jichao Zhang +1
Facial attribute editing aims to manipulate attributes on the human face, e.g., adding a mustache or changing the hair color. Existing approaches suffer from a serious compromise b…
AttGAN: Facial Attribute Editing by Only Changing What You Want
Zhenliang He, Wangmeng Zuo, Meina Kan +2
Facial attribute editing aims to manipulate single or multiple attributes of a face image, i.e., to generate a new face with desired attributes while preserving other details. Rece…
Funnel-Structured Cascade for Multi-View Face Detection with Alignment-Awareness
Shuzhe Wu, Meina Kan, Zhenliang He +2
Multi-view face detection in open environment is a challenging task due to diverse variations of face appearances and shapes. Most multi-view face detectors depend on multiple mode…