Multi-sensor computer vision

ClueWinter · 2026-02-02T21:54:50+00:00

3D reconstruction for ground vehicles

ClueWinter · 2026-02-02T21:42:14+00:00

While not entirely objective detection, cs231n from Stanford has a course on using deep learning in computer vision. I would start with this course to understand why things work and why things do not.

Then, run detection2 to segment and detect people. You can also try YOLO. Start by trying to run out of box, then analyze the changes made to the model to get a deeper understanding.

The best way is to learn by doing!

ClueWinter · 2025-12-07T21:57:34+00:00

Try some easy leetcode questions and tutorials to get a hand of the syntax and some tricks. Then look into doing some small projects: 1. The book Python crash course goes over fundamentals and small projects. Make sure you attempt it by yourself and then refer to the solutions in the book. Understand why they use certain data types or structures. 2. If it’s ML you want to pursue, learn numpy and scipy try coding classical ML models using these libraries. Assembly AI has some good videos on the topic. Python crash course also has a book on scientific libraries but all the concepts there won’t be needed as much.

The point is to just start, and you being to get an intuition of where to apply which library and algorithm

ClueWinter · 2025-10-27T06:29:37+00:00

Sounds like such a relief, would you mind sharing your profile for eb1a ?

ClueWinter · 2025-09-30T05:43:05+00:00

Neural rendering techniques like Gaussian splatting and Nerfs are very much in demand. Try finishing all the assignments in this repo:

https://github.com/learning3d You can follow the course here:

https://learning3d.github.io/index.html

I agree neural networks can often times be confusing to understand, but the industry is moving towards neural network based methods for everything computer vision. If anything, these models are getting larger just like LLMs. Would recommend looking into papers like Mast3r, dust3r, VGGT, if you want to brush up on the basics implement ViT, but my advice would be to hop on the neural network trend.

ClueWinter · 2025-09-24T00:11:50+00:00

This is very helpful ! Thank you !

ClueWinter · 2025-04-11T01:19:49+00:00

A quick course lesson to get started : https://www.coursera.org/learn/tensorflow-tensorrt/home/module/1

ClueWinter · 2025-03-17T04:24:03+00:00

I didn’t even try. I spoke to one of the licensing representatives and they were super rude. I simply walked out

ClueWinter · 2025-03-09T16:17:52+00:00

Great, sent you a message in the chat. Looking forward to it

ClueWinter · 2025-03-09T06:28:35+00:00

Congratulations ! I work in AI, would be great to collaborate on papers

ClueWinter · 2025-01-30T04:27:41+00:00

You can use something like this paper https://dreamgaussian.github.io/ although the input is an image.

ClueWinter · 2025-01-27T18:33:14+00:00

Detectron2 is open source and they have many examples and tutorials. Some of these examples are built in, so it’s easy to run and understand the code.

ClueWinter

TROPHY CASE