Deep Learning/CV

Learning based computer vision

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Computer vision project overview

An overview of computer vision tasks.

Welcome to the showcase of my deep learning and computer vision projects, where innovation meets practical application. My portfolio spans a variety of cutting-edge projects that demonstrate my expertise in harnessing the power of neural networks to interpret and understand visual data. From developing sophisticated algorithms for real-time object detection and recognition, to crafting advanced neural network architectures for image segmentation and enhancement, each project embodies my commitment to advancing the field of computer vision.

Learning-based vision

Superpixels and SLIC

Superpixels and SLIC

Segmentation using superpixels.
Generative Adversarial Networks

Generative Adversarial Networks

GANs on MNIST and DCGANs on a human faces dataset.
LiDAR SLAM

LiDAR SLAM

Simultaneous localization and mapping using LiDAR data.

Semantic Segmentation and Object Detection

Semantic Segmentation

Semantic Segmentation

Sample segmentation results.
Object Detection

Object Detection

Sample object detection results.

Representation and geometry

Implicit Neural Representation

Implicit Neural Representation

An MLP predicts an RGB pixel value from its x and y coordinates, representing an image as a continuous function.
Structure from Motion

Structure from Motion
Pose Estimation

Pose Estimation

Classical Computer Vision

K-Means Clustering
Stereo Depth Estimation
Lane detection
Trajectory Tracking
Zhang’s Camera Calibration
Tsai Camera Calibration
Image Stitching
Camera Pose Estimation