986 citations · 1.6k across the 52 of their papers we have counts for
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A Real-time Global Inference Network for One-stage Referring Expression Comprehension
Yiyi Zhou, Rongrong Ji, Gen Luo +5
Referring Expression Comprehension (REC) is an emerging research spot in computer vision, which refers to detecting the target region in an image given an text description. Most ex…
Learning Rate Dropout
Huangxing Lin, Weihong Zeng, Xinghao Ding +3
The performance of a deep neural network is highly dependent on its training, and finding better local optimal solutions is the goal of many optimization algorithms. However, exist…
Noise2Blur: Online Noise Extraction and Denoising
Huangxing Lin, Weihong Zeng, Xinghao Ding +3
We propose a new framework called Noise2Blur (N2B) for training robust image denoising models without pre-collected paired noisy/clean images. The training of the model requires on…
Multi-sequence Cardiac MR Segmentation with Adversarial Domain Adaptation Network
Jiexiang Wang, Hongyu Huang, Chaoqi Chen +3
Automatic and accurate segmentation of the ventricles and myocardium from multi-sequence cardiac MRI (CMR) is crucial for the diagnosis and treatment management for patients suffer…
Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images
Jiexiang Wang, Cheng Bian, Meng Li +6
Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases. However, because of…
Unsupervised Adversarial Graph Alignment with Graph Embedding
Chaoqi Chen, Weiping Xie, Tingyang Xu +5
Graph alignment, also known as network alignment, is a fundamental task in social network analysis. Many recent works have relied on partially labeled cross-graph node corresponden…
Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes
Chengquan Zhang, Borong Liang, Zuming Huang +4
Previous scene text detection methods have progressed substantially over the past years. However, limited by the receptive field of CNNs and the simple representations like rectang…
Rain O'er Me: Synthesizing real rain to derain with data distillation
Huangxing Lin, Yanlong Li, Xinghao Ding +3
We present a supervised technique for learning to remove rain from images without using synthetic rain software. The method is based on a two-stage data distillation approach: 1) A…