商汤感知算法实习生
实习兼职算法研究地点：上海状态：招聘
包括英文材料
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
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!
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.
学历+
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
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.
相关职位
实习
1. 机器人感知算法的数据处理，模型训练和优化； 2. 完善数据质量、模型性能评估体系，建立能够覆盖实际场景的评测系统； 3. 搭建自动化数据标注，数据生产闭环系统。
更新于 2025-07-01
实习
1. 负责自动驾驶业务场景下的感知算法研发，调研跟进前沿算法，辅助业务落地，包括但不限于： a）激光雷达3D多任务感知，如3D Object Detection，3D Semantic Segmentation， 3D Occupancy Flow Prediction, EndToEnd, World Model等； b）BEV视觉感知和前融合算法，如BEVDet，BEVFusion，Occupancy Network等； c）感知全链路研发，如跟踪，多传感器融合等； 2. 负责自动驾驶数据算法研发，助力数据自动化生产和4D真值构建，包括单不限于： a) SLAM/SFM算法研发； b) 基于Deep Learning的MonoDepth/Multi-View Stereo算法研发； c）NerF相关算法研发； d）大模型AIGC、LMM、NerF、3D Gaussian生成等技术研发； 3. 将相关结果总结沉淀，发表高水平论文 。
更新于 2025-05-07
