14 citations · 16 across the 4 of their papers we have counts for
5 papers
HetSeq: Distributed GPU Training on Heterogeneous Infrastructure
Yifan Ding, Nicholas Botzer, Tim Weninger
Modern deep learning systems like PyTorch and Tensorflow are able to train enormous models with billions (or trillions) of parameters on a distributed infrastructure. These systems…
Self-supervised learning for audio-visual speaker diarization
Yifan Ding, Yong Xu, Shi-Xiong Zhang +2
Speaker diarization, which is to find the speech segments of specific speakers, has been widely used in human-centered applications such as video conferences or human-computer inte…
Defending Against Adversarial Attacks Using Random Forests
Yifan Ding, Liqiang Wang, Huan Zhang +3
As deep neural networks (DNNs) have become increasingly important and popular, the robustness of DNNs is the key to the safety of both the Internet and the physical world. Unfortun…
Frame-Recurrent Video Inpainting by Robust Optical Flow Inference
Yifan Ding, Chuan Wang, Haibin Huang +3
In this paper, we present a new inpainting framework for recovering missing regions of video frames. Compared with image inpainting, performing this task on video presents new chal…
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation
Jiaming Liu, Chi-Hao Wu, Yuzhi Wang +8
In this paper, we present new data pre-processing and augmentation techniques for DNN-based raw image denoising. Compared with traditional RGB image denoising, performing this task…