149 citations · 184 across the 13 of their papers we have counts for
8 papers · 1 filter
Unsupervised Domain Adaptation for Anatomical Landmark Detection
Haibo Jin, Haoxuan Che, Hao Chen
Recently, anatomical landmark detection has achieved great progresses on single-domain data, which usually assumes training and test sets are from the same domain. However, such an…
PromptMRG: Diagnosis-Driven Prompts for Medical Report Generation
Haibo Jin, Haoxuan Che, Yi Lin +1
Automatic medical report generation (MRG) is of great research value as it has the potential to relieve radiologists from the heavy burden of report writing. Despite recent advance…
Towards Generalizable Diabetic Retinopathy Grading in Unseen Domains
Haoxuan Che, Yuhan Cheng, Haibo Jin +1
Diabetic Retinopathy (DR) is a common complication of diabetes and a leading cause of blindness worldwide. Early and accurate grading of its severity is crucial for disease managem…
Learning Robust Representation for Joint Grading of Ophthalmic Diseases via Adaptive Curriculum and Feature Disentanglement
Haoxuan Che, Haibo Jin, Hao Chen
Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of permanent blindness worldwide. Designing an automatic grading system with good generalization abili…
Fight Perturbations with Perturbations: Defending Adversarial Attacks via Neuron Influence
Ruoxi Chen, Haibo Jin, Haibin Zheng +2
The vulnerabilities of deep learning models towards adversarial attacks have attracted increasing attention, especially when models are deployed in security-critical domains. Numer…
When Liebig's Barrel Meets Facial Landmark Detection: A Practical Model
Haibo Jin, Jinpeng Li, Shengcai Liao +1
In recent years, significant progress has been made in the research of facial landmark detection. However, few prior works have thoroughly discussed about models for practical appl…
Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild
Haibo Jin, Shengcai Liao, Ling Shao
Recently, heatmap regression models have become popular due to their superior performance in locating facial landmarks. However, three major problems still exist among these models…
Deep Person Re-Identification with Improved Embedding and Efficient Training
Haibo Jin, Xiaobo Wang, Shengcai Liao +1
Person re-identification task has been greatly boosted by deep convolutional neural networks (CNNs) in recent years. The core of which is to enlarge the inter-class distinction as…