27 citations · 59 across the 9 of their papers we have counts for
9 papers
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Wangbo Zhao, Xinai Lu +8
Class distribution mismatch (CDM) refers to the discrepancy between class distributions in training data and target tasks. Previous methods address this by designing classifiers to…
Boosting Binary Neural Networks via Dynamic Thresholds Learning
Jiehua Zhang, Xueyang Zhang, Zhuo Su +5
Developing lightweight Deep Convolutional Neural Networks (DCNNs) and Vision Transformers (ViTs) has become one of the focuses in vision research since the low computational cost i…
Improving Image Restoration by Revisiting Global Information Aggregation
Xiaojie Chu, Liangyu Chen, Chengpeng Chen +1
Global operations, such as global average pooling, are widely used in top-performance image restorers. They aggregate global information from input features along entire spatial di…
Dynamic Binary Neural Network by learning channel-wise thresholds
Jiehua Zhang, Zhuo Su, Yanghe Feng +3
Binary neural networks (BNNs) constrain weights and activations to +1 or -1 with limited storage and computational cost, which is hardware-friendly for portable devices. Recently,…
Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Kim Byeoung-su, Radu Timofte +29
Image denoising is one of the most critical problems in mobile photo processing. While many solutions have been proposed for this task, they are usually working with synthetic data…
HINet: Half Instance Normalization Network for Image Restoration
Liangyu Chen, Xin Lu, Jie Zhang +2
In this paper, we explore the role of Instance Normalization in low-level vision tasks. Specifically, we present a novel block: Half Instance Normalization Block (HIN Block), to bo…