1.2k citations · 1.2k across the 6 of their papers we have counts for
6 papers
Many-to-Many Matching via Sparsity Controlled Optimal Transport
Weijie Liu, Han Bao, Makoto Yamada +3
Many-to-many matching seeks to match multiple points in one set and multiple points in another set, which is a basis for a wide range of data mining problems. It can be naturally r…
ClassPruning: Speed Up Image Restoration Networks by Dynamic N:M Pruning
Yang Zhou, Yuda Song, Hui Qian +1
Image restoration tasks have achieved tremendous performance improvements with the rapid advancement of deep neural networks. However, most prevalent deep learning models perform i…
Rethinking Performance Gains in Image Dehazing Networks
Yuda Song, Yang Zhou, Hui Qian +1
Image dehazing is an active topic in low-level vision, and many image dehazing networks have been proposed with the rapid development of deep learning. Although these networks' pip…
Vision Transformers for Single Image Dehazing
Yuda Song, Zhuqing He, Hui Qian +1
Image dehazing is a representative low-level vision task that estimates latent haze-free images from hazy images. In recent years, convolutional neural network-based methods have d…
Multi-Curve Translator for High-Resolution Photorealistic Image Translation
Yuda Song, Hui Qian, Xin Du
The dominant image-to-image translation methods are based on fully convolutional networks, which extract and translate an image's features and then reconstruct the image. However,…
StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement
Yuda Song, Hui Qian, Xin Du
Image enhancement is a subjective process whose targets vary with user preferences. In this paper, we propose a deep learning-based image enhancement method covering multiple tonal…