
地平线4D 视觉重建算法实习生
实习兼职算法序列地点:上海状态:招聘
任职要求
1. 硕士/博士在读,计算机、人工智能、自动化、机器人、测绘、数学等相关专业优先。实习时间半年及以上。 2. 具备扎实的深度学习、计算机视觉和三维几何基础,熟悉多视图几何、SfM/MVS、深度估计、点云处理或三维重建相关方法。 3. 熟练使用 Python / PyTorch,具备良好的代码能力和实验分析能力,能够独立阅读、复现并改进顶会论文。 4. 对 VGGT、Dust3R、MASt3R、DROID-SLAM、3DGS、NeRF、CoTracker、UniDepth 等方向有理解或实践经验者优先。 加分项 1. 有 3D scene flow、dynamic recon…
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工作职责
1. 参与基于 VGGT / Dust3R 等视觉重建 backbone 的 3D 点云场景流与动态 4D 重建算法研发,探索多帧几何一致性、动态物体运动建模与时空特征融合。 2. 跟踪并复现 3D/4D 视觉前沿方法,如 TraceAnything、V-DPM、4RC、D4RT、3DGS、Neural Rendering、Feed-forward Reconstruction 等,参与方案设计与技术选型。 3. 搭建自动驾驶场景下的数据处理、模型训练、评测分析与可视化流程,推动算法在真实数据和闭环仿真场景中的快速落地。
包括英文材料
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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.
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.
SLAM+
https://docs.mrpt.org/reference/latest/tutorial-slam-for-beginners-the-basics.html
[英文] SLAM for Dummies
https://dspace.mit.edu/bitstream/handle/1721.1/119149/16-412j-spring-2005/contents/projects/1aslam_blas_repo.pdf
A Tutorial Approach to Simultaneous Localization and Mapping
https://ouster.com/insights/blog/introduction-to-slam-simultaneous-localization-and-mapping
SLAM is an essential piece in robotics that helps robots to estimate their pose – the position and orientation – on the map while creating the map of the environment to carry out autonomous activities.
[英文] What Is SLAM?
https://www.mathworks.com/discovery/slam.html
How it works, types of SLAM algorithms, and getting started
Framer Motion+
https://motion.dev/docs/quick-start
Motion is an animation library that's easy to start and fun to master.
https://www.youtube.com/watch?v=znbCa4Rr054
Framer Motion is not only the simplest way to get up and running with animations in React JS, but also one of the most powerful.
还有更多 •••