9 citations · 39 across the 6 of their papers we have counts for
7 papers
Representing Noisy Image Without Denoising
Shuren Qi, Yushu Zhang, Chao Wang +3
A long-standing topic in artificial intelligence is the effective recognition of patterns from noisy images. In this regard, the recent data-driven paradigm considers 1) improving…
Joint Linear and Nonlinear Computation across Functions for Efficient Privacy-Preserving Neural Network Inference
Qiao Zhang, Tao Xiang, Chunsheng Xin +2
While it is encouraging to witness the recent development in privacy-preserving Machine Learning as a Service (MLaaS), there still exists a significant performance gap for its depl…
Style-Based Global Appearance Flow for Virtual Try-On
Sen He, Yi-Zhe Song, Tao Xiang
Image-based virtual try-on aims to fit an in-shop garment into a clothed person image. To achieve this, a key step is garment warping which spatially aligns the target garment with…
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
Ayan Kumar Bhunia, Subhadeep Koley, Abdullah Faiz Ur Rahman Khilji +4
Sketching enables many exciting applications, notably, image retrieval. The fear-to-sketch problem (i.e., "I can't sketch") has however proven to be fatal for its widespread adopti…
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Shangwei Guo, Xu Zhang, Fei Yang +4
With the rapid demand of data and computational resources in deep learning systems, a growing number of algorithms to utilize collaborative machine learning techniques, for example…
Hybrid Graph Neural Networks for Few-Shot Learning
Tianyuan Yu, Sen He, Yi-Zhe Song +1
Graph neural networks (GNNs) have been used to tackle the few-shot learning (FSL) problem and shown great potentials under the transductive setting. However under the inductive set…
Protecting Your NLG Models with Semantic and Robust Watermarks
Tao Xiang, Chunlong Xie, Shangwei Guo +2
Natural language generation (NLG) applications have gained great popularity due to the powerful deep learning techniques and large training corpus. The deployed NLG models may be s…