腾讯技术研究-计算机视觉方向
校招全职应届生地点：深圳 | 北京 | 上海 | 广州状态：招聘
任职要求
1、包含但不限于计算机、信息工程、模式识别、人工智能、自动化、软件工程、电子工程、统计学、应用数学、物理学/量子计算、信息安全、信号与信息处理等专业的博士和优秀硕士； 2、熟练掌握计算机视觉和图像处理相关的基本算法及应用，熟悉caffe、tensorflow，pytorch等至少一个深度学习框架； 3、较强的工程实现能力，熟练掌握 C/C++ 编程，熟悉 Shell/Python/Matlab 至少一种编程语言。 加分项 在CVPR、ICCV、ECCV、ICML、NeurIPS、COLT等计算机视觉、机器学习学术会议或期刊以第一作者发表过文章、有丰富项目经验。
工作职责
作为计算机视觉方向的研究工程师，你可以： 1、负责图像/视频相关算法的研究与开发，包括深度学习以及常用机器学习方法在机器视觉中的应用； 2、负责计算机视觉相关的技术研发工作，包括但不限于：人脸识别、物体检测、分类、语义分割和图像处理、人体（活体）识别、车辆与人员的检测识别与跟踪、图像/视频搜索、视频语义分析、视频特征提取与识别、页面分析与自动合成、OCR等算法与系统研发领域； 3、负责深度学习、图像理解、机器学习等前沿技术的研发储备和平台建设，结合未来实际应用场景，提供技术解决方案。
包括英文材料
模式识别+
https://www.mathworks.com/discovery/pattern-recognition.html
Pattern recognition is the process of classifying input data into objects, classes, or categories using computer algorithms based on key features or regularities.
https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science.
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
图像处理+
https://opencv.org/blog/computer-vision-and-image-processing/
This fascinating journey involves two key fields: Computer Vision and Image Processing.
https://www.geeksforgeeks.org/python/image-processing-in-python/
Image processing involves analyzing and modifying digital images using computer algorithms.
https://www.youtube.com/watch?v=kSqxn6zGE0c
In this Introduction to Image Processing with Python, kaggle grandmaster Rob Mulla shows how to work with image data in python!
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
TensorFlow+
https://www.youtube.com/watch?v=tpCFfeUEGs8
Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
https://www.youtube.com/watch?v=ZUKz4125WNI
This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.
PyTorch+
https://datawhalechina.github.io/thorough-pytorch/
PyTorch是利用深度学习进行数据科学研究的重要工具，在灵活性、可读性和性能上都具备相当的优势，近年来已成为学术界实现深度学习算法最常用的框架。
https://www.youtube.com/watch?v=V_xro1bcAuA
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
C+
https://www.freecodecamp.org/chinese/news/the-c-beginners-handbook/
本手册遵循二八定律。你将在 20% 的时间内学习 80% 的 C 编程语言。
https://www.youtube.com/watch?v=87SH2Cn0s9A
https://www.youtube.com/watch?v=KJgsSFOSQv0
This course will give you a full introduction into all of the core concepts in the C programming language.
https://www.youtube.com/watch?v=PaPN51Mm5qQ
In this complete C programming course, Dr. Charles Severance (aka Dr. Chuck) will help you understand computer architecture and low-level programming with the help of the classic C Programming language book written by Brian Kernighan and Dennis Ritchie.
C+++
https://www.learncpp.com/
LearnCpp.com is a free website devoted to teaching you how to program in modern C++.
https://www.youtube.com/watch?v=ZzaPdXTrSb8
Bash+
[英文] The Bash Guide
https://guide.bash.academy/
A quality-driven guide through the shell's many features.
https://www.youtube.com/watch?v=tK9Oc6AEnR4
Understanding how to use bash scripting will enhance your productivity by automating tasks, streamlining processes, and making your workflow more efficient.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文，免费，零起点，完整示例，基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
MATLAB+
https://matlabacademy.mathworks.com/?page=1&sort=featured
Learn MATLAB and Simulink through interactive, in-product exercises
https://www.mathworks.com/help/matlab/getting-started-with-matlab.html
Millions of engineers and scientists worldwide use MATLAB® to analyze and design the systems and products transforming our world.
https://www.youtube.com/watch?v=7f50sQYjNRA
Learn the fundametnals of MATLAB in this tutorial for engineers, scientists, and students.
CVPR+
https://cvpr.thecvf.com/
ICCV+
https://iccv.thecvf.com/
ICCV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials.
ECCV+
https://eccv.ecva.net/
ECCV is the official event under the European Computer Vision Association and is biannual on even numbered years.
ICML+
https://icml.cc/
NeurIPS+
https://neurips.cc/
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
相关职位
实习实习生
作为计算机视觉方向的研究工程师，你可以： 1、负责图像/视频相关算法的研究与开发，包括深度学习以及常用机器学习方法在机器视觉中的应用； 2、负责计算机视觉相关的技术研发工作，包括但不限于：人脸识别、物体检测、分类、语义分割和图像处理、人体（活体）识别、车辆与人员的检测识别与跟踪、图像/视频搜索、视频语义分析、视频特征提取与识别、页面分析与自动合成、OCR等算法与系统研发领域； 3、负责深度学习、图像理解、机器学习等前沿技术的研发储备和平台建设，结合未来实际应用场景，提供技术解决方案。
校招青云计划-实习生
作为计算机视觉方向的研究工程师，你可以： 1、负责图像/视频相关算法的研究与开发，包括深度学习以及常用机器学习方法在机器视觉中的应用； 2、负责计算机视觉相关的技术研发工作，包括但不限于：人脸识别、物体检测、分类、语义分割和图像处理、人体（活体）识别、车辆与人员的检测识别与跟踪、图像/视频搜索、视频语义分析、视频特征提取与识别、页面分析与自动合成、OCR等算法与系统研发领域； 3、负责深度学习、图像理解、机器学习等前沿技术的研发储备和平台建设，结合未来实际应用场景，提供技术解决方案。
校招青云计划-应届生
作为计算机视觉方向的研究工程师，你可以： 1、负责图像/视频相关算法的研究与开发，包括深度学习以及常用机器学习方法在机器视觉中的应用； 2、负责计算机视觉相关的技术研发工作，包括但不限于：人脸识别、物体检测、分类、语义分割和图像处理、人体（活体）识别、车辆与人员的检测识别与跟踪、图像/视频搜索、视频语义分析、视频特征提取与识别、页面分析与自动合成、OCR等算法与系统研发领域； 3、负责深度学习、图像理解、机器学习等前沿技术的研发储备和平台建设，结合未来实际应用场景，提供技术解决方案。
实习通义研究型实习生
4D Gaussian Splatting（4D GS）作为一种极具前景的新兴动态场景重建技术，近年来受到广泛关注，并取得了显著进展。然而，实现实时训练与渲染仍是该领域面临的核心挑战。本项目拟结合大规模数据驱动的大模型训练与高度优化的3D Gaussian Splatting技术，以多视角视频为输入，在秒级时间内完成动态场景的高质量重建，并支持自由视角与任意时间点的图像渲染。
更新于 2025-10-17