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Definition of Reputation Credits
陳昱希
Computer Vision Engineer
Yu-Hsi Chen has rich experience in developing computer vision and machine learning algorithms. In his recent work at Academia Sinica, he has focused on using machine learning to solve traditional computer vision and image / video processing problems. His developed NeighborTrack is a state-of-the-art single object tracking system in the field. During his school days, he used verilog on FPGA to implement the 3A system of the camera.
website: Yu-hsi Chen (franktpmvu.github.io)
Taipei City, Taiwan
Yu-hsi Chen (franktpmvu.github.io)
Publications
- NeighborTrack: Single Object Tracking by Bipartite Matching With Neighbor Tracklets and Its Applications to Sports [code]
Yu-Hsi Chen, Chien-Yao Wang, Cheng-Yun Yang, Hung-Shuo Chang, Youn-Long Lin, Yung-Yu Chuang, Hong-Yuan Mark Liao
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR), 2023 - A multiresolution approach to recovering colors and details of clipped image regions
Yi-Hung Lu, Yu-Hsi Chen, Hsueh-Yi Sean Lin
In International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP), 2015 - Full-Frame Video Stabilization via SIFT Feature Matching (Excellent Paper Awards)
Yu-Hsi Chen, Hsueh-Yi Sean Lin, and Chih Wen Su
In International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP), 2014
工作經歷
Computer Vision Engineer • Academia Sinica
. Developed and improved many state-of-the-art deep learning models CNN, C3D, Siamese Network, Transformer, and YOLO series in Python3 and PyTorch.
. Top Achievement : NeighborTrack Che 22, the most accurate single-object tracking method in the world.
. Research scope : Computer Vision : Object detection/tracking, Person Re-Identification and Video Stabilization.
Projects:
Single object tracking 03 2021
I.I.S. Research, Framework:python/pytorch
• Designed a post-processing method NeighborTrack[CVPR2023] to introduce neighbor and temporal
information to alleviate the error tracking of single object tracking.
• Proved NeighborTrack is the state-of-the-art single-object tracking model as the accuracy on LaSOT is
72.2% AUC. NeighborTrack: Single Object Tracking by Bipartite Matching With Neighbor Tracklets and Its Applications to Sports [code]
Multiple object tracking 08 2019
I.I.S. Research, Framework:python/pytorch
• Used multi-scale features and non-local net in unknown class multiple object tracking to Improve base
method accuracy.
• Improved the base model by 1.2x Average Precision (33% to 40%) in MOT17 dataset.
Video based fall detection 04 2019
I.I.S. Research, Framework:python/tensorflow
• Implemented optical flow features and data augmentation to improve the accuracy of C3D-pelee deep
learning network in fall detection tasks.
• Increased the accuracy of the basic network, UCF101 dataset from 57.1 to 59.5, MCF dataset from 85.4 to
87.5.
Video person Re-ID 04 2018
I.I.S. Research, Team work, Framework:python/tensorflow on embedding system Jetson TX2
• Adapted the mobilenetV2 person ReID system to the embedded system Jetson TX2, which has only 7% of
the computing power of the desktop computer GPU RTX 1080TI.
• Participated in AISlanders’ Show 2018 and CES 2019.
Emotion reading system 06 2016
I.I.S. Research, Framework:python/caffee
• Combined face detection and emotion recognition to build a speaker assistance system that captures
audience emotions in real time and provides feedback.
Video Stabilization[IIHMSP] 08 2014
Master’s Thesis, Framework:MATLAB
• Implemented SIFT feature matching to get the camera movement path and update it to a stable path with
content-preserving warping.
• Submitted to IIHMSP2014 and won the Excellent paper award. Full-Frame Video Stabilization via SIFT Feature Matching (Excellent Paper Awards)
High-Dynamic Range image mapping 05 2013
Senior project, Framework:MATLAB
• Developed a MATLAB-based HDR system using histogram equalization and entropy to map an HDR.
Camera Automatic Exposure and Automatic White Balance 09 2012
Senior project, Team Leader, Framework: quatus verilog on embedding system DE2-70
• Implemented verilog for an AE and AWB camera system on an FPGA-based embedded system.
• Led four students to participate in the FPGA contest held by Altera asia.
一月 2015 - 一月 2023
學歷
2013 - 2015
LUNGHWA university
Master of Science
2009 - 2013
LUNGHWA university
Bachelor of Computer Information and Network Engineering
技能
- Provides Feedback
- Communication
- Precision
- Team Work
- Research
- Focused
- Machine Learning Algorithms
- Image/Video Processing
- Information Science
- Learning Network
語言
- Chinese - Native
- English - Elementary
陳昱希
Computer Vision Engineer
Yu-Hsi Chen has rich experience in developing computer vision and machine learning algorithms. In his recent work at Academia Sinica, he has focused on using machine learning to solve traditional computer vision and image / video processing problems. His developed NeighborTrack is a state-of-the-art single object tracking system in the field. During his school days, he used verilog on FPGA to implement the 3A system of the camera.
website: Yu-hsi Chen (franktpmvu.github.io)
Taipei City, Taiwan
Yu-hsi Chen (franktpmvu.github.io)
Publications
- NeighborTrack: Single Object Tracking by Bipartite Matching With Neighbor Tracklets and Its Applications to Sports [code]
Yu-Hsi Chen, Chien-Yao Wang, Cheng-Yun Yang, Hung-Shuo Chang, Youn-Long Lin, Yung-Yu Chuang, Hong-Yuan Mark Liao
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR), 2023 - A multiresolution approach to recovering colors and details of clipped image regions
Yi-Hung Lu, Yu-Hsi Chen, Hsueh-Yi Sean Lin
In International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP), 2015 - Full-Frame Video Stabilization via SIFT Feature Matching (Excellent Paper Awards)
Yu-Hsi Chen, Hsueh-Yi Sean Lin, and Chih Wen Su
In International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP), 2014
工作經歷
Computer Vision Engineer • Academia Sinica
. Developed and improved many state-of-the-art deep learning models CNN, C3D, Siamese Network, Transformer, and YOLO series in Python3 and PyTorch.
. Top Achievement : NeighborTrack Che 22, the most accurate single-object tracking method in the world.
. Research scope : Computer Vision : Object detection/tracking, Person Re-Identification and Video Stabilization.
Projects:
Single object tracking 03 2021
I.I.S. Research, Framework:python/pytorch
• Designed a post-processing method NeighborTrack[CVPR2023] to introduce neighbor and temporal
information to alleviate the error tracking of single object tracking.
• Proved NeighborTrack is the state-of-the-art single-object tracking model as the accuracy on LaSOT is
72.2% AUC. NeighborTrack: Single Object Tracking by Bipartite Matching With Neighbor Tracklets and Its Applications to Sports [code]
Multiple object tracking 08 2019
I.I.S. Research, Framework:python/pytorch
• Used multi-scale features and non-local net in unknown class multiple object tracking to Improve base
method accuracy.
• Improved the base model by 1.2x Average Precision (33% to 40%) in MOT17 dataset.
Video based fall detection 04 2019
I.I.S. Research, Framework:python/tensorflow
• Implemented optical flow features and data augmentation to improve the accuracy of C3D-pelee deep
learning network in fall detection tasks.
• Increased the accuracy of the basic network, UCF101 dataset from 57.1 to 59.5, MCF dataset from 85.4 to
87.5.
Video person Re-ID 04 2018
I.I.S. Research, Team work, Framework:python/tensorflow on embedding system Jetson TX2
• Adapted the mobilenetV2 person ReID system to the embedded system Jetson TX2, which has only 7% of
the computing power of the desktop computer GPU RTX 1080TI.
• Participated in AISlanders’ Show 2018 and CES 2019.
Emotion reading system 06 2016
I.I.S. Research, Framework:python/caffee
• Combined face detection and emotion recognition to build a speaker assistance system that captures
audience emotions in real time and provides feedback.
Video Stabilization[IIHMSP] 08 2014
Master’s Thesis, Framework:MATLAB
• Implemented SIFT feature matching to get the camera movement path and update it to a stable path with
content-preserving warping.
• Submitted to IIHMSP2014 and won the Excellent paper award. Full-Frame Video Stabilization via SIFT Feature Matching (Excellent Paper Awards)
High-Dynamic Range image mapping 05 2013
Senior project, Framework:MATLAB
• Developed a MATLAB-based HDR system using histogram equalization and entropy to map an HDR.
Camera Automatic Exposure and Automatic White Balance 09 2012
Senior project, Team Leader, Framework: quatus verilog on embedding system DE2-70
• Implemented verilog for an AE and AWB camera system on an FPGA-based embedded system.
• Led four students to participate in the FPGA contest held by Altera asia.
一月 2015 - 一月 2023
學歷
2013 - 2015
LUNGHWA university
Master of Science
2009 - 2013
LUNGHWA university
Bachelor of Computer Information and Network Engineering
技能
- Provides Feedback
- Communication
- Precision
- Team Work
- Research
- Focused
- Machine Learning Algorithms
- Image/Video Processing
- Information Science
- Learning Network
語言
- Chinese - Native
- English - Elementary