most citedRobust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness

17 citations · 39 across the 7 of their papers we have counts for

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cs.CV20201 cited

Improving Object Detection with Selective Self-supervised Self-training

Yandong Li, Di Huang, Danfeng Qin +2

We study how to leverage Web images to augment human-curated object detection datasets. Our approach is two-pronged. On the one hand, we retrieve Web images by image-to-image searc…

cs.CV2020

BachGAN: High-Resolution Image Synthesis from Salient Object Layout

Yandong Li, Yu Cheng, Zhe Gan +3

We propose a new task towards more practical application for image generation - high-quality image synthesis from salient object layout. This new setting allows users to provide th…

cs.CV20195 cited

AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning

Yunhui Guo, Yandong Li, Liqiang Wang +1

There is an increasing number of pre-trained deep neural network models. However, it is still unclear how to effectively use these models for a new task. Transfer learning, which a…

cs.CV2019

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…

cs.CV201917 cited

Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness

Adnan Siraj Rakin, Zhezhi He, Li Yang +3

Deep Neural Network (DNN) trained by the gradient descent method is known to be vulnerable to maliciously perturbed adversarial input, aka. adversarial attack. As one of the counte…

cs.CV201914 cited

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…