11 citations · 12 across the 4 of their papers we have counts for
6 papers · 1 filter
Addressing Imbalance for Class Incremental Learning in Medical Image Classification
Xuze Hao, Wenqian Ni, Xuhao Jiang +2
Deep convolutional neural networks have made significant breakthroughs in medical image classification, under the assumption that training samples from all classes are simultaneous…
Context-Aware Iteration Policy Network for Efficient Optical Flow Estimation
Ri Cheng, Ruian He, Xuhao Jiang +3
Existing recurrent optical flow estimation networks are computationally expensive since they use a fixed large number of iterations to update the flow field for each sample. An eff…
MVFlow: Deep Optical Flow Estimation of Compressed Videos with Motion Vector Prior
Shili Zhou, Xuhao Jiang, Weimin Tan +2
In recent years, many deep learning-based methods have been proposed to tackle the problem of optical flow estimation and achieved promising results. However, they hardly consider…
Uncertainty-Guided Spatial Pruning Architecture for Efficient Frame Interpolation
Ri Cheng, Xuhao Jiang, Ruian He +3
The video frame interpolation (VFI) model applies the convolution operation to all locations, leading to redundant computations in regions with easy motion. We can use dynamic spat…
Multi-Modality Deep Network for JPEG Artifacts Reduction
Xuhao Jiang, Weimin Tan, Qing Lin +3
In recent years, many convolutional neural network-based models are designed for JPEG artifacts reduction, and have achieved notable progress. However, few methods are suitable for…
Deep Optimization model for Screen Content Image Quality Assessment using Neural Networks
Xuhao Jiang, Liquan Shen, Guorui Feng +2
In this paper, we propose a novel quadratic optimized model based on the deep convolutional neural network (QODCNN) for full-reference and no-reference screen content image (SCI) q…