36 citations · 121 across the 25 of their papers we have counts for
25 papers
WMFormer++: Nested Transformer for Visible Watermark Removal via Implict Joint Learning
Dongjian Huo, Zehong Zhang, Hanjing Su +3
Watermarking serves as a widely adopted approach to safeguard media copyright. In parallel, the research focus has extended to watermark removal techniques, offering an adversarial…
Identity-Preserving Talking Face Generation with Landmark and Appearance Priors
Weizhi Zhong, Chaowei Fang, Yinqi Cai +4
Generating talking face videos from audio attracts lots of research interest. A few person-specific methods can generate vivid videos but require the target speaker's videos for tr…
Calibrating Undisciplined Over-Smoothing in Transformer for Weakly Supervised Semantic Segmentation
Lechao Cheng, Zerun Liu, Jingxuan He +3
Weakly supervised semantic segmentation (WSSS) has recently attracted considerable attention because it requires fewer annotations than fully supervised approaches, making it espec…
Revisiting Long-tailed Image Classification: Survey and Benchmarks with New Evaluation Metrics
Chaowei Fang, Dingwen Zhang, Wen Zheng +4
Recently, long-tailed image classification harvests lots of research attention, since the data distribution is long-tailed in many real-world situations. Piles of algorithms are de…
Compound Batch Normalization for Long-tailed Image Classification
Lechao Cheng, Chaowei Fang, Dingwen Zhang +2
Significant progress has been made in learning image classification neural networks under long-tail data distribution using robust training algorithms such as data re-sampling, re-…
Combating Noisy Labels in Long-Tailed Image Classification
Chaowei Fang, Lechao Cheng, Huiyan Qi +1
Most existing methods that cope with noisy labels usually assume that the class distributions are well balanced, which has insufficient capacity to deal with the practical scenario…
Deep 3D Vessel Segmentation based on Cross Transformer Network
Chengwei Pan, Baolian Qi, Gangming Zhao +4
The coronary microvascular disease poses a great threat to human health. Computer-aided analysis/diagnosis systems help physicians intervene in the disease at early stages, where 3…
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance
Chengwei Pan, Gangming Zhao, Junjie Fang +6
Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to mu…
Cross-Modality High-Frequency Transformer for MR Image Super-Resolution
Chaowei Fang, Dingwen Zhang, Liang Wang +3
Improving the resolution of magnetic resonance (MR) image data is critical to computer-aided diagnosis and brain function analysis. Higher resolution helps to capture more detailed…
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation
Xinkai Zhao, Chaowei Fang, De-Jun Fan +3
Semi-supervised learning (SSL), which aims at leveraging a few labeled images and a large number of unlabeled images for network training, is beneficial for relieving the burden of…
Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis
Chaowei Fang, Liang Wang, Dingwen Zhang +3
Due to the constraints of the imaging device and high cost in operation time, computer tomography (CT) scans are usually acquired with low intra-slice resolution. Improving the int…
Weakly Supervised Semantic Segmentation via Alternative Self-Dual Teaching
Dingwen Zhang, Wenyuan Zeng, Guangyu Guo +4
Current weakly supervised semantic segmentation (WSSS) frameworks usually contain the separated mask-refinement model and the main semantic region mining model. These approaches wo…
MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions
Penghua Zhai, Huaiwei Cong, Gangming Zhao +4
\emph{Objective and Impact Statement}. With the renaissance of deep learning, automatic diagnostic systems for computed tomography (CT) have achieved many successful applications.…
Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning
Junkai Huang, Chaowei Fang, Weikai Chen +5
Open-set semi-supervised learning (open-set SSL) investigates a challenging but practical scenario where out-of-distribution (OOD) samples are contained in the unlabeled data. Whil…
GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-ray Images
Baolian Qi, Gangming Zhao, Xin Wei +4
Locating diseases in chest X-ray images with few careful annotations saves large human effort. Recent works approached this task with innovative weakly-supervised algorithms such a…
Deep Transformers for Fast Small Intestine Grounding in Capsule Endoscope Video
Xinkai Zhao, Chaowei Fang, Feng Gao +3
Capsule endoscopy is an evolutional technique for examining and diagnosing intractable gastrointestinal diseases. Because of the huge amount of data, analyzing capsule endoscope vi…
Densely Nested Top-Down Flows for Salient Object Detection
Chaowei Fang, Haibin Tian, Dingwen Zhang +3
With the goal of identifying pixel-wise salient object regions from each input image, salient object detection (SOD) has been receiving great attention in recent years. One kind of…
Contralaterally Enhanced Networks for Thoracic Disease Detection
Gangming Zhao, Chaowei Fang, Guanbin Li +2
Identifying and locating diseases in chest X-rays are very challenging, due to the low visual contrast between normal and abnormal regions, and distortions caused by other overlapp…
A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution
Hongying Liu, Zhubo Ruan, Chaowei Fang +4
Spherical videos, also known as \ang{360} (panorama) videos, can be viewed with various virtual reality devices such as computers and head-mounted displays. They attract large amou…
PNEN: Pyramid Non-Local Enhanced Networks
Feida Zhu, Chaowei Fang, Kai-Kuang Ma
Existing neural networks proposed for low-level image processing tasks are usually implemented by stacking convolution layers with limited kernel size. Every convolution layer mere…
Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics
Dou Xu, Chang Cai, Chaowei Fang +3
Annotating histopathological images is a time-consuming andlabor-intensive process, which requires broad-certificated pathologistscarefully examining large-scale whole-slide images…
Meta Corrupted Pixels Mining for Medical Image Segmentation
Jixin Wang, Sanping Zhou, Chaowei Fang +2
Deep neural networks have achieved satisfactory performance in piles of medical image analysis tasks. However the training of deep neural network requires a large amount of samples…
Self-Enhanced Convolutional Network for Facial Video Hallucination
Chaowei Fang, Guanbin Li, Xiaoguang Han +1
As a domain-specific super-resolution problem, facial image hallucination has enjoyed a series of breakthroughs thanks to the advances of deep convolutional neural networks. Howeve…
Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation
Chaowei Fang, Guanbin Li, Chengwei Pan +2
Recently 3D volumetric organ segmentation attracts much research interest in medical image analysis due to its significance in computer aided diagnosis. This paper aims to address…