PyTorch-based toolkit for landmark detection
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Updated
May 28, 2024 - Python
PyTorch-based toolkit for landmark detection
The implementation of part of the ORB (Oriented FAST and Rotated BRIEF) pipeline. The ORB consists of the feature detector and feature descriptor that detect and describe reproducible and discriminative regions in an image. Those, in turn, can be matched between pairs of images for correspondence search, 3D reconstruction, and so on.
Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629
A simple and minimal posenet inference in python
This work generates 2D and 3D landmark labels from videos with only two or three uncalibrated, handheld cameras moving in the wild. NeurIPS 2022.
Keypoint-matching (AKAZE method) using OpenCV library
WACV 2023: Centroid Distance Keypoint Detector for Colored Point Clouds
Monitor Your Workout through a Webcam/IP Camera. No equipment is required, other than a camera and a laptop. This application could potentially replace a personal trainer, making it the idea app for workout.
Implementation of various human pose estimation models in pytorch on multiple datasets (MPII & COCO) along with pretrained models
3D object tracking using keypoint detection and feature matching, lidar point cloud data, and image classification using YOLO deep learning model.
Build the feature tracking part of a collision detection system, and test various combinations of keypoint detectors and descriptors to see which combinations perform best.
🏀🤖🏀 AI web app and API to analyze basketball shots and shooting pose on google colab
Swap face between two photos.
This is SRHandNet demo source code written in python3
A new approach to multi-scale template matching using key-point matching and perspective-transformations
Feature Tracking and testing of various keypoint detector/descriptor combinations, keypoint matching using Brute Force and FLANN approach.
SOLOv2: Dynamic, Faster and Stronger. achieve 37.2mAP on coco val (res50,36 epoch) Adding keypoints
Estimating trajectory using RGB-D images
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