Jintao Lin
Research Intern at 上海人工智能实验室
Xuhui District, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolJintao Lin is a research-focused computer vision engineer with eight years of experience specializing in video understanding and action recognition, now expanding into vision-and-language multimodal research at Shanghai AI Lab. He has been a core maintainer for OpenMMLab projects (MMCV and MMAction2), contributing video-processing features, dataset pipelines, motion-vector support, and NonLocal module implementations used widely by the community. With a strong academic record from Harbin Institute of Technology and ongoing graduate study at Nanjing University, he combines rigorous theory with practical tooling that improves large-scale video ingestion and model complexity analysis. Notably, his open-source work added URL-based video processing and efficient decoding modes, reflecting a focus on real-world data pipelines as much as model design.
8 years of coding experience
硕士, 计算机科学, 硕士, 计算机科学 at 南京大学学士学位, 计算机科学, Rank 1/70, GPA 3.87/4.0, 学士学位, 计算机科学, Rank 1/70, GPA 3.87/4.0 at 哈尔滨工业大学
Github Skills (8)
computer-vision10
pytorch10
machine-learning10
data-pipeline10
data-pipelines10
python10
unit-testing9
video-processing7
Programming languages (6)
Github contributions (5)
open-mmlab/mmaction2
Dec 2019 - Jun 2022
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:3 releases, 696 reviews, 595 commits in 2 years 5 months
Contributions summary:Jintao's commits primarily focus on adding datasets and enhancing data pipelines for a video understanding toolbox. The contributions include incorporating new datasets, particularly the addition of the UCF101 and other datasets, and implementing support for both accurate and efficient video decoding modes. Furthermore, they are responsible for adding tools to prepare datasets, alongside work in support for motion vectors. This indicates a focus on improving the data ingestion and processing capabilities for video-related machine learning tasks.
avax3dvisual-recognitionbenchmarkvideo
open-mmlab/mmcv
May 2020 - Jul 2021
OpenMMLab Computer Vision Foundation
Role in this project:ML Engineer
ML EngineerContributions:23 reviews, 29 commits, 30 PRs in 1 year 2 months
Contributions summary:Jintao primarily contributed to the `mmcv` repository, which is a foundation for computer vision projects. Their work focused on enhancing the codebase with new functionalities for NonLocal modules, including different modes like 'gaussian' and 'concatenation', and related unit tests. They added support for video processing from URLs. The user also addressed model complexity calculation utilities and improved the integration of the core library's functions.
visiondeep-learningcomputer-visionfoundationopenmmlab
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