Peize Sun
Member Of Technical Staff at xAI
Hong Kong Island, Hong Kong, United States
Summary
🤩
Rockstar🎓
Top SchoolPeize Sun is a computer vision-focused ML engineer and PhD candidate at The University of Hong Kong, now a Member of Technical Staff at xAI with six years of research and engineering experience. They have held research roles at Meta and internships at ByteDance, Cruise and MEGVII, contributing across both industry-scale systems and academic projects. An active open-source contributor, Peize implemented core tracking modules for the widely-cited ByteTrack (ECCV 2022) and fixed inference and loss issues in SparseR-CNN (CVPR 2021), demonstrating expertise in multi-object tracking, association strategies and production-ready inference. Based in Hong Kong Island, they bridge algorithmic rigor with pragmatic engineering to optimize model robustness and deployment.
7 years of coding experience
1 year of employment as a software developer
The University of Hong Kong (HKU)Master of Engineering - MEng, Electrical Engineering, Master of Engineering - MEng, Electrical Engineering at Xi'an Jiaotong University
Github Skills (10)
multi-object-tracking10
object-detection10
computer-vision10
pytorch10
python10
kalman-filter10
rgba9
rgb9
mask-rcnn9
faster-rcnn9
Programming languages (4)
Github contributions (5)
PeizeSun/SparseR-CNN
Nov 2020 - Sep 2021
End-to-End Object Detection with Learnable Proposal, CVPR2021
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 2 reviews, 72 commits in 9 months
Contributions summary:Peize primarily contributed to the object detection model within the SparseR-CNN project. They focused on bug fixes related to the inference process and focal loss, and modified input image formats to RGB. This demonstrates a focus on model refinement and ensuring the code runs as intended. The user also updated the codebase to align with existing conventions.
pytorchend-to-endobject-detectioncomputer-visionfaster-rcnn
ifzhang/ByteTrack
Aug 2021 - Oct 2021
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:110 commits in 1 month
Contributions summary:Peize implemented `cstrack.py`, `cstrack_new.py` and modified other associated files, indicating a focus on the core tracking functionality. The files suggest implementation of object tracking algorithms, potentially involving Kalman filters and related matching strategies. The changes directly relate to the core purpose of the project (multi-object tracking), suggesting development and enhancement of the tracking algorithms.
pytorchboxdeploymenteccvobject-detection
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