74 citations · 233 across the 15 of their papers we have counts for
15 papers
Lightweight network towards real-time image denoising on mobile devices
Zhuoqun Liu, Meiguang Jin, Ying Chen +3
Deep convolutional neural networks have achieved great progress in image denoising tasks. However, their complicated architectures and heavy computational cost hinder their deploym…
Class-Specific Channel Attention for Few-Shot Learning
Ying-Yu Chen, Jun-Wei Hsieh, Ming-Ching Chang
Few-Shot Learning (FSL) has attracted growing attention in computer vision due to its capability in model training without the need for excessive data. FSL is challenging because t…
Mask-based Data Augmentation for Semi-supervised Semantic Segmentation
Ying Chen, Xu Ouyang, Kaiyue Zhu +1
Semantic segmentation using convolutional neural networks (CNN) is a crucial component in image analysis. Training a CNN to perform semantic segmentation requires a large amount of…
Domain Adaptation on Semantic Segmentation for Aerial Images
Ying Chen, Xu Ouyang, Kaiyue Zhu +1
Semantic segmentation has achieved significant advances in recent years. While deep neural networks perform semantic segmentation well, their success rely on pixel level supervisio…
MANGO: A Mask Attention Guided One-Stage Scene Text Spotter
Liang Qiao, Ying Chen, Zhanzhan Cheng +4
Recently end-to-end scene text spotting has become a popular research topic due to its advantages of global optimization and high maintainability in real applications. Most methods…
Cascade Attentive Dropout for Weakly Supervised Object Detection
Wenlong Gao, Ying Chen, Yong Peng
Weakly supervised object detection (WSOD) aims to classify and locate objects with only image-level supervision. Many WSOD approaches adopt multiple instance learning as the initia…