3 citations · 10 across the 6 of their papers we have counts for
6 papers
Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution
Xufei Wang, Fei Ge, Jinchen Zhu +3
Methods based on implicit neural representation have demonstrated remarkable capabilities in arbitrary-scale super-resolution (ASSR) tasks, but they neglect the potential value of…
Realistic Noise Synthesis with Diffusion Models
Qi Wu, Mingyan Han, Ting Jiang +5
Deep denoising models require extensive real-world training data, which is challenging to acquire. Current noise synthesis techniques struggle to accurately model complex noise dis…
DIPNet: Efficiency Distillation and Iterative Pruning for Image Super-Resolution
Lei Yu, Xinpeng Li, Youwei Li +4
Efficient deep learning-based approaches have achieved remarkable performance in single image super-resolution. However, recent studies on efficient super-resolution have mainly fo…
Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution
Ziwei Luo, Youwei Li, Lei Yu +4
Deep learning-based single image super-resolution (SISR) approaches have drawn much attention and achieved remarkable success on modern advanced GPUs. However, most state-of-the-ar…
Foreground-Background Imbalance Problem in Deep Object Detectors: A Review
Joya Chen, Qi Wu, Dong Liu +1
Recent years have witnessed the remarkable developments made by deep learning techniques for object detection, a fundamentally challenging problem of computer vision. Nevertheless,…
Deep Template Matching for Offline Handwritten Chinese Character Recognition
Zhiyuan Li, Min Jin, Qi Wu +1
Just like its remarkable achievements in many computer vision tasks, the convolutional neural networks (CNN) provide an end-to-end solution in handwritten Chinese character recogni…