116 citations · 128 across the 7 of their papers we have counts for
7 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…
SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement
Canqian Yang, Meiguang Jin, Yi Xu +3
Image-adaptive lookup tables (LUTs) have achieved great success in real-time image enhancement tasks due to their high efficiency for modeling color transforms. However, they embed…
AdaInt: Learning Adaptive Intervals for 3D Lookup Tables on Real-time Image Enhancement
Canqian Yang, Meiguang Jin, Xu Jia +2
The 3D Lookup Table (3D LUT) is a highly-efficient tool for real-time image enhancement tasks, which models a non-linear 3D color transform by sparsely sampling it into a discretiz…
Interventional Multi-Instance Learning with Deconfounded Instance-Level Prediction
Tiancheng Lin, Hongteng Xu, Canqian Yang +1
When applying multi-instance learning (MIL) to make predictions for bags of instances, the prediction accuracy of an instance often depends on not only the instance itself but also…
Self Supervised Lesion Recognition For Breast Ultrasound Diagnosis
Yuanfan Guo, Canqian Yang, Tiancheng Lin +3
Previous deep learning based Computer Aided Diagnosis (CAD) system treats multiple views of the same lesion as independent images. Since an ultrasound image only describes a partia…
Decoupled Gradient Harmonized Detector for Partial Annotation: Application to Signet Ring Cell Detection
Tiancheng Lin, Yuanfan Guo, Canqian Yang +2
Early diagnosis of signet ring cell carcinoma dramatically improves the survival rate of patients. Due to lack of public dataset and expert-level annotations, automatic detection o…
Reinventing 2D Convolutions for 3D Images
Jiancheng Yang, Xiaoyang Huang, Yi He +4
There have been considerable debates over 2D and 3D representation learning on 3D medical images. 2D approaches could benefit from large-scale 2D pretraining, whereas they are gene…