I got a chance to attend CVPR 2024 (remotely). I posted my version of highlights on my Medium.

Here are the links:

• CVPR 2024 highlights on structure from motion
• CVPR 2024 Keynotes
• CVPR 2024 selected paper highlights
• CVPR 2024 papers on action anticipation

Modeling light as rays is widely used in computer graphics and lens design. I encountered this problem when I tried to do some optical design but had no access to commercial ray-tracing software, such as ZEMAX OpticStudio or LightTools. During my attempt of implementing a ray-tracing program for my own …

This is my attempt of a past Kaggle competition Lyft 3D Object Detection for Autonomous Vehicles, using the concept of frustum-pointnet to solve this past Kaggle competition.

This is an example of the classifed results:

Result

This work is still in progress. The result does not seem too bad if …

I did this project partly for Udacity's Self-Driving car degree and was lazy to train and retraing a DNN model. It ends up that this solution is not so lazy, but I did learn some details and traps of using a HSV or HSL color space.

I posted the writing-up …

This is a project with Udacity's Self-Driving Car Nanodegree. The aim is to identify the lane lines on the road and get their curvatures, using an algorithmic (i.e. non-machine learning) way.

Here's the result of the baseline video:

and here's the results on a more challenging scene:

Code and …

The aim of this project is to implement a car that drives automatically in a simulation world. The car should be able to switch the lane smoothly when necessary. I think this is the most fun and challenging project of Udacity Self-Driving Car Nanodegree.

The code repo and the explanation …

This is a project with Udacity's Self-Driving Car Nanodegree. The aim is to use deep learning approach[1] to clone the behaviour of a car in the simulator made by Udacity. To get a good data set, I have to "drive" well in the simulator, and use this dataset to …