11 citations · 16 across the 6 of their papers we have counts for
6 papers
SEA: Bridging the Gap Between One- and Two-stage Detector Distillation via SEmantic-aware Alignment
Yixin Chen, Zhuotao Tian, Pengguang Chen +2
We revisit the one- and two-stage detector distillation tasks and present a simple and efficient semantic-aware framework to fill the gap between them. We address the pixel-level i…
Adversarial Attacks on ML Defense Models Competition
Yinpeng Dong, Qi-An Fu, Xiao Yang +25
Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…
Deep Structured Instance Graph for Distilling Object Detectors
Yixin Chen, Pengguang Chen, Shu Liu +2
Effectively structuring deep knowledge plays a pivotal role in transfer from teacher to student, especially in semantic vision tasks. In this paper, we present a simple knowledge s…
Exploring and Improving Mobile Level Vision Transformers
Pengguang Chen, Yixin Chen, Shu Liu +2
We study the vision transformer structure in the mobile level in this paper, and find a dramatic performance drop. We analyze the reason behind this phenomenon, and propose a novel…
Distilling Knowledge via Knowledge Review
Pengguang Chen, Shu Liu, Hengshuang Zhao +1
Knowledge distillation transfers knowledge from the teacher network to the student one, with the goal of greatly improving the performance of the student network. Previous methods…
Jigsaw Clustering for Unsupervised Visual Representation Learning
Pengguang Chen, Shu Liu, Jiaya Jia
Unsupervised representation learning with contrastive learning achieved great success. This line of methods duplicate each training batch to construct contrastive pairs, making eac…