19 citations · 28 across the 8 of their papers we have counts for
8 papers
One-Class Model for Fabric Defect Detection
Hao Zhou, Yixin Chen, David Troendle +1
An automated and accurate fabric defect inspection system is in high demand as a replacement for slow, inconsistent, error-prone, and expensive human operators in the textile indus…
Learning Convolutional Neural Networks in the Frequency Domain
Hengyue Pan, Yixin Chen, Xin Niu +2
Convolutional neural network (CNN) has achieved impressive success in computer vision during the past few decades. The image convolution operation helps CNNs to get good performanc…
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…
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Grigory Malivenko, Radu Timofte +28
Camera scene detection is among the most popular computer vision problem on smartphones. While many custom solutions were developed for this task by phone vendors, none of the desi…
Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Radu Timofte, Maurizio Denna +20
Image super-resolution is one of the most popular computer vision problems with many important applications to mobile devices. While many solutions have been proposed for this task…
DEPARA: Deep Attribution Graph for Deep Knowledge Transferability
Jie Song, Yixin Chen, Jingwen Ye +4
Exploring the intrinsic interconnections between the knowledge encoded in PRe-trained Deep Neural Networks (PR-DNNs) of heterogeneous tasks sheds light on their mutual transferabil…
Deep Model Transferability from Attribution Maps
Jie Song, Yixin Chen, Xinchao Wang +2
Exploring the transferability between heterogeneous tasks sheds light on their intrinsic interconnections, and consequently enables knowledge transfer from one task to another so a…