Virtual environment segmentation
Computer Vision, Semantic Segmentation, 2024
This project, based on Stanford’s computer vision course, utilizes the KITTI dataset—a collection of images and LIDAR data for autonomous driving research.
The focus is on semantic segmentation, where a U-Net model pre-trained on ImageNet is fine-tuned on the KITTI dataset. This approach aims to enhance the model’s ability to interpret complex driving scenes. The code and images are available in this GitHub repository.
Link to the gihub repository:
