3 citations · 7 across the 5 of their papers we have counts for
5 papers
PFL-GAN: When Client Heterogeneity Meets Generative Models in Personalized Federated Learning
Achintha Wijesinghe, Songyang Zhang, Zhi Ding
Recent advances of generative learning models are accompanied by the growing interest in federated learning (FL) based on generative adversarial network (GAN) models. In the contex…
UFed-GAN: A Secure Federated Learning Framework with Constrained Computation and Unlabeled Data
Achintha Wijesinghe, Songyang Zhang, Siyu Qi +1
To satisfy the broad applications and insatiable hunger for deploying low latency multimedia data classification and data privacy in a cloud-based setting, federated learning (FL)…
PS-FedGAN: An Efficient Federated Learning Framework Based on Partially Shared Generative Adversarial Networks For Data Privacy
Achintha Wijesinghe, Songyang Zhang, Zhi Ding
Federated Learning (FL) has emerged as an effective learning paradigm for distributed computation owing to its strong potential in capturing underlying data statistics while preser…
Temporal Segment Transformer for Action Segmentation
Zhichao Liu, Leshan Wang, Desen Zhou +5
Recognizing human actions from untrimmed videos is an important task in activity understanding, and poses unique challenges in modeling long-range temporal relations. Recent works…
Action Quality Assessment with Temporal Parsing Transformer
Yang Bai, Desen Zhou, Songyang Zhang +5
Action Quality Assessment(AQA) is important for action understanding and resolving the task poses unique challenges due to subtle visual differences. Existing state-of-the-art meth…