10 citations · 69 across the 17 of their papers we have counts for
6 papers · 1 filter
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network
Wenjie Li, Juncheng Li, Guangwei Gao +4
Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss…
Meta Transferring for Deblurring
Po-Sheng Liu, Fu-Jen Tsai, Yan-Tsung Peng +3
Most previous deblurring methods were built with a generic model trained on blurred images and their sharp counterparts. However, these approaches might have sub-optimal deblurring…
A heterogeneous group CNN for image super-resolution
Chunwei Tian, Yanning Zhang, Wangmeng Zuo +3
Convolutional neural networks (CNNs) have obtained remarkable performance via deep architectures. However, these CNNs often achieve poor robustness for image super-resolution (SR)…
Magic ELF: Image Deraining Meets Association Learning and Transformer
Kui Jiang, Zhongyuan Wang, Chen Chen +3
Convolutional neural network (CNN) and Transformer have achieved great success in multimedia applications. However, little effort has been made to effectively and efficiently harmo…
Image Super-resolution with An Enhanced Group Convolutional Neural Network
Chunwei Tian, Yixuan Yuan, Shichao Zhang +3
CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to improve performance of image supe…
Stripformer: Strip Transformer for Fast Image Deblurring
Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin +2
Images taken in dynamic scenes may contain unwanted motion blur, which significantly degrades visual quality. Such blur causes short- and long-range region-specific smoothing artif…