40 citations · 97 across the 17 of their papers we have counts for
8 papers · 1 filter
The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Yan Shu +60
This paper reviews the NTIRE 2026 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a…
Completed Feature Disentanglement Learning for Multimodal MRIs Analysis
Tianling Liu, Hongying Liu, Fanhua Shang +3
Multimodal MRIs play a crucial role in clinical diagnosis and treatment. Feature disentanglement (FD)-based methods, aiming at learning superior feature representations for multimo…
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer
Zhijin Ge, Fanhua Shang, Hongying Liu +4
Deep neural networks are vulnerable to adversarial examples crafted by applying human-imperceptible perturbations on clean inputs. Although many attack methods can achieve high suc…
Boosting Adversarial Transferability by Achieving Flat Local Maxima
Zhijin Ge, Hongying Liu, Xiaosen Wang +2
Transfer-based attack adopts the adversarial examples generated on the surrogate model to attack various models, making it applicable in the physical world and attracting increasin…
Quantized Neural Networks via {-1, +1} Encoding Decomposition and Acceleration
Qigong Sun, Xiufang Li, Fanhua Shang +4
The training of deep neural networks (DNNs) always requires intensive resources for both computation and data storage. Thus, DNNs cannot be efficiently applied to mobile phones and…
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling
Hongying Liu, Peng Zhao, Zhubo Ruan +2
Video super-resolution (VSR) aims at restoring a video in low-resolution (LR) and improving it to higher-resolution (HR). Due to the characteristics of video tasks, it is very impo…
Video Super Resolution Based on Deep Learning: A Comprehensive Survey
Hongying Liu, Zhubo Ruan, Peng Zhao +5
In recent years, deep learning has made great progress in many fields such as image recognition, natural language processing, speech recognition and video super-resolution. In this…
signADAM: Learning Confidences for Deep Neural Networks
Dong Wang, Yicheng Liu, Wenwo Tang +4
In this paper, we propose a new first-order gradient-based algorithm to train deep neural networks. We first introduce the sign operation of stochastic gradients (as in sign-based…