Haifang Qin - Personal Homepage (Liquid Design)

About Me

Hello, I'm Haifang. I am currently working at Disney+, focusing mainly on Computer Vision area. I completed my Bachelor's degree at Peking University in 2016, and later pursued my Master's degree under the guidance of Prof. Yuru Pei, which I obtained in 2019. Following that, I worked at Sensetime Ltd for around 2 years, where I specialized in autonomous driving with a primary focus on perception research.

My research interests are diverse and encompass two areas: object detection and instance segmentation of common objects, as well as medical image analysis involving registration and segmentation. I am deeply committed to making a meaningful impact in these fields and actively seek opportunities for collaboration.

Publications

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Deformable registration of lateral cephalogram and cone‑beam computed tomography image

Yungeng Zhang, Haifang Qin, Peixin Li, Yuru Pei, Yuke Guo, Tianmin Xu, and Hongbin Zha

Medical Physics, 2021

Paper
Image hashing via linear discriminant learning

Weixiang Hong, Yu-Ting Chang, Haifang Qin, Wei-Chih Hung, Yi-Hsuan Tsai, and Ming-Hsuan Yang

Proceedings of the IEEE/CVF winter conference on applications of computer vision (WACV), 2020

Paper
Masseter Muscle Segmentation from Cone-Beam CT Images using Generative Adversarial Network

Yungeng Zhang, Yuru Pei, Haifang Qin, Yuke Guo, Gengyu Ma,Tianmin Xu and Hongbin Zha

International Symposium on Biomedical Imaging (ISBI), 2019

Paper
A Top-Down Unified Framework for Instance-level Human Parsing

Haifang Qin*, Weixiang Hong*, Wei-Chih Hung, Yi-Hsuan Tsai, and Ming-Hsuan Yang

British Machine Vision Conference (BMVC), 2019

Paper
Masseter segmentation from computed tomography using feature-enhanced nested residual neural network

Haifang Qin, Yuru Pei, Yuke Guo, Gengyu Ma, Tianmin Xu, and Hongbin Zha

Machine Learning in Medical Imaging (MLMI), 2018

Paper
Path Aggregation Network for Instance Segmentation

Shu Liu*, Lu Qi*, Haifang Qin*, Jianping Shi^†, and Jiaya Jia^†

Computer Vision and Pattern Recognition (CVPR), 2018 (Spotlight)

Paper Code
Temporal consistent 2D-3D registration of lateral cephalograms and cone-beam computed tomography images

Yungeng Zhang, Yuru Pei, Haifang Qin, Yuke Guo, Gengyu Ma, Tianmin Xu, and Hongbin Zha

Machine Learning in Medical Imaging (MLMI), 2018

Paper
Multi-scale volumetric ConvNet with nested residual connections for segmentation of anterior cranial base

Yuru Pei, Haifang Qin, Gengyu Ma, Yuke Guo, Gui Chen, Tianmin Xu, and Hongbin Zha

Machine Learning in Medical Imaging (MLMI), 2017

Paper
Non-rigid craniofacial 2D-3D registration using CNN-based regression

Yuru Pei, Yungeng Zhang, Haifang Qin*, Gengyu Ma Yuke Guo, Tianmin Xu, and Hongbin Zha*

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop (DLMIA), 2017

Paper

Haifang Qin 秦海芳

About Me

Publications

Deformable registration of lateral cephalogram and cone‑beam computed tomography image

Image hashing via linear discriminant learning

Masseter Muscle Segmentation from Cone-Beam CT Images using Generative Adversarial Network

A Top-Down Unified Framework for Instance-level Human Parsing

Masseter segmentation from computed tomography using feature-enhanced nested residual neural network

Path Aggregation Network for Instance Segmentation

Temporal consistent 2D-3D registration of lateral cephalograms and cone-beam computed tomography images

Multi-scale volumetric ConvNet with nested residual connections for segmentation of anterior cranial base

Non-rigid craniofacial 2D-3D registration using CNN-based regression

Awards and Honors