地平线感知算法实习生(OCC方向)-base上海/南京
实习兼职算法序列地点：南京 | 上海状态：招聘
任职要求
1、计算机视觉、机器学习、机器人、电子工程等相关专业，硕士/博士在读； 2、熟悉以下1-2种 3D 表征或 3D 场景建模方式： occupancy / OccFlow / 4D Occupancy / NeRF / 3DGS 场景流估计（Scene Flow） BEV 与 3D 感知 时序场建模（Temporal Conv / Transformer / Flow-based） 3、熟练掌握主流深度学习框架（PyTorch / TensorFlow）； 4、有扎实的深度学习基础，理解 Tran…
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工作职责
1、负责基于 Occupancy / OccFlow / 3D 场景理解的感知模型研发，包括：
Occupancy Network（静态/动态）、OccFlow 时空场建模
3D 表征学习（voxel / BEV / GS）
3D foundation models & 多模态融合（LiDAR / Camera / Radar）
2、设计和训练大规模 3D 场景模型：负责数据构建、模型结构设计、并行训练等；
3、跟踪 3D 表征、BEV、OccFlow、NeRF、3D/4D GS 等领域的最新研究成果，并推动在业务中的快速验证与落地；包括英文材料
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.
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.
Transformer+
https://huggingface.co/learn/llm-course/en/chapter1/4
Breaking down how Large Language Models work, visualizing how data flows through.
https://poloclub.github.io/transformer-explainer/
An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.
https://www.youtube.com/watch?v=wjZofJX0v4M
Breaking down how Large Language Models work, visualizing how data flows through.
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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.
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.
CNN+
https://learnopencv.com/understanding-convolutional-neural-networks-cnn/
Convolutional Neural Network (CNN) forms the basis of computer vision and image processing.
[英文] CNN Explainer
https://poloclub.github.io/cnn-explainer/
Learn Convolutional Neural Network (CNN) in your browser!
https://www.deeplearningbook.org/contents/convnets.html
Convolutional networks(LeCun, 1989), also known as convolutional neuralnetworks, or CNNs, are a specialized kind of neural network for processing data.
https://www.youtube.com/watch?v=2xqkSUhmmXU
MIT Introduction to Deep Learning 6.S191: Lecture 3 Convolutional Neural Networks for Computer Vision
还有更多 •••
相关职位
实习算法序列
3D视觉方向【base地：上海/北京/南京】 1、负责面向端到端驾驶环境感知前沿算法的研发工作，包括不限于目标检测、语义分割、目标跟踪，深度估计，重建、世界模型等； 2、负责面向端到端自动驾驶多传感器（包括不限于视觉/Lidar/Radar)融合感知算法的探索与研发； 3、负责研究自动驾驶场景中端到端感知任务的模型的优化； 4、负责计算机视觉领域前沿技术中网络模型分析和研究工作；
更新于 2025-11-28北京|南京|上海
实习技术
1、负责自动驾驶系统中BEV（鸟瞰图）感知算法的研发与落地，包括但不限于2D/3D目标检测、语义分割、深度估计、OCC、车道线检测等任务； 2、基于视觉、激光雷达（LiDAR）或融合传感器数据，设计并优化BEV特征表示与感知模型，提升复杂场景下的环境理解能力； 3、研究并实现BEV感知算法的轻量化部署（如模型压缩、加速推理），满足车端实时性与算力约束； 4、跟踪学术前沿（如OCC、NeRF、Diffusion模型），推动算法创新并应用于实际业务场景。
更新于 2025-09-08上海
