318 citations · 361 across the 6 of their papers we have counts for
6 papers
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
Jie Liu, Yixiao Zhang, Jie-Neng Chen +7
An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection. However, due to the small size and partially labeled problem…
AdaDM: Enabling Normalization for Image Super-Resolution
Jie Liu, Jie Tang, Gangshan Wu
Normalization like Batch Normalization (BN) is a milestone technique to normalize the distributions of intermediate layers in deep learning, enabling faster training and better gen…
Edge-Cloud Collaborated Object Detection via Difficult-Case Discriminator
Zhiqiang Cao, Zhijun Li, Pan Heng +3
As one of the basic tasks of computer vision, object detection has been widely used in many intelligent applications. However, object detection algorithms are usually heavyweight i…
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…
Anchor-based Plain Net for Mobile Image Super-Resolution
Zongcai Du, Jie Liu, Jie Tang +1
Along with the rapid development of real-world applications, higher requirements on the accuracy and efficiency of image super-resolution (SR) are brought forward. Though existing…
Residual Feature Distillation Network for Lightweight Image Super-Resolution
Jie Liu, Jie Tang, Gangshan Wu
Recent advances in single image super-resolution (SISR) explored the power of convolutional neural network (CNN) to achieve a better performance. Despite the great success of CNN-b…