Xin Ding

According to our database, Xin Ding authored at least 17 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Hyper adversarial tuning for boosting adversarial robustness of pretrained large vision transformers.

Kangtao Lv, Wenyan Fan, Huangsen Cao, Kainan Tu, Yihuai Xu, Zhimeng Zhang, Yang Li, Xin Ding, Yongwei Wang

Pattern Recognit., 2026

2025

Tri-Memristor Hyperchaotic Ring Neural Network With Hidden Firings: Dynamic Analysis, Hardware Implementation, and Application to Image Encryption.

Jie Wang, Sen Zhang, Yuanjin Zheng, Yongxin Li, Chunbiao Li, Yichen Wang, Xin Ding

IEEE Internet Things J., November, 2025

Imbalance-Robust and Sampling-Efficient Continuous Conditional GANs via Adaptive Vicinity and Auxiliary Regularization.

Xin Ding, Yun Chen, Yongwei Wang, Kao Zhang, Sen Zhang, Peibei Cao, Xiangxue Wang

CoRR, August, 2025

2024

HyperDet: Generalizable Detection of Synthesized Images by Generating and Merging A Mixture of Hyper LoRAs.

Huangsen Cao, Yongwei Wang, Yinfeng Liu, Sixian Zheng, Kangtao Lv, Zhimeng Zhang, Bo Zhang, Xin Ding, Fei Wu

CoRR, 2024

Hyper Adversarial Tuning for Boosting Adversarial Robustness of Pretrained Large Vision Models.

Kangtao Lv, Huangsen Cao, Kainan Tu, Yihuai Xu, Zhimeng Zhang, Xin Ding, Yongwei Wang

CoRR, 2024

CCDM: Continuous Conditional Diffusion Models for Image Generation.

Xin Ding, Yongwei Wang, Kao Zhang, Z. Jane Wang

CoRR, 2024

Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks.

Xin Ding, Yongwei Wang, Zuheng Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input Mechanisms.

Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

Distilling and transferring knowledge via cGAN-generated samples for image classification and regression.

Xin Ding, Yongwei Wang, Zuheng Xu, Z. Jane Wang, William J. Welch

Expert Syst. Appl., March, 2023

Efficient subsampling of realistic images from GANs conditional on a class or a continuous variable.

Xin Ding, Yongwei Wang, Z. Jane Wang, William J. Welch

Neurocomputing, 2023

2021

Perception matters: Exploring imperceptible and transferable anti-forensics for GAN-generated fake face imagery detection.

Yongwei Wang, Xin Ding, Yixin Yang, Li Ding, Rabab Ward, Z. Jane Wang

Pattern Recognit. Lett., 2021

Efficient Subsampling for Generating High-Quality Images from Conditional Generative Adversarial Networks.

Xin Ding, Yongwei Wang, Z. Jane Wang, William J. Welch

CoRR, 2021

Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework.

Li Ding, Yongwei Wang, Xin Ding, Kaiwen Yuan, Ping Wang, Hua Huang, Z. Jane Wang

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

CcGAN: Continuous Conditional Generative Adversarial Networks for Image Generation.

Xin Ding, Yongwei Wang, Zuheng Xu, William J. Welch, Z. Jane Wang

Proceedings of the 9th International Conference on Learning Representations, 2021

Classification Beats Regression: Counting of Cells from Greyscale Microscopic Images Based on Annotation-Free Training Samples.

Xin Ding, Qiong Zhang, William J. Welch

Proceedings of the Artificial Intelligence - First CAAI International Conference, 2021

2020

Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space With Softplus Loss.

Xin Ding, Z. Jane Wang, William J. Welch

IEEE Trans. Signal Process., 2020

Perception Matters: Exploring Imperceptible and Transferable Anti-forensics for GAN-generated Fake Face Imagery Detection.

Yongwei Wang, Xin Ding, Li Ding, Rabab Ward, Z. Jane Wang

CoRR, 2020