2 citations · 4 across the 7 of their papers we have counts for
7 papers
Any-Size-Diffusion: Toward Efficient Text-Driven Synthesis for Any-Size HD Images
Qingping Zheng, Yuanfan Guo, Jiankang Deng +4
Stable diffusion, a generative model used in text-to-image synthesis, frequently encounters resolution-induced composition problems when generating images of varying sizes. This is…
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data
Minghao Xu, Yuanfan Guo, Yi Xu +3
Modeling spatial relationship in the data remains critical across many different tasks, such as image classification, semantic segmentation and protein structure understanding. Pre…
HIRL: A General Framework for Hierarchical Image Representation Learning
Minghao Xu, Yuanfan Guo, Xuanyu Zhu +5
Learning self-supervised image representations has been broadly studied to boost various visual understanding tasks. Existing methods typically learn a single level of image semant…
Enhancing Non-mass Breast Ultrasound Cancer Classification With Knowledge Transfer
Yangrun Hu, Yuanfan Guo, Fan Zhang +4
Much progress has been made in the deep neural network (DNN) based diagnosis of mass lesions breast ultrasound (BUS) images. However, the non-mass lesion is less investigated becau…
Self Supervised Lesion Recognition For Breast Ultrasound Diagnosis
Yuanfan Guo, Canqian Yang, Tiancheng Lin +3
Previous deep learning based Computer Aided Diagnosis (CAD) system treats multiple views of the same lesion as independent images. Since an ultrasound image only describes a partia…
HCSC: Hierarchical Contrastive Selective Coding
Yuanfan Guo, Minghao Xu, Jiawen Li +4
Hierarchical semantic structures naturally exist in an image dataset, in which several semantically relevant image clusters can be further integrated into a larger cluster with coa…