41 results for “topic:keypoints-detector”
Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629
Implementation of various human pose estimation models in pytorch on multiple datasets (MPII & COCO) along with pretrained models
Full pipeline for TianChi FashionAI clothes keypoints detection compitetion in TensorFlow
Basic demo of Vector Field Consensus method for image keypoint matching
FSRK : Fast Spherical Retina Keypoint
PyTorch-based toolkit for landmark localization
WACV 2023: Centroid Distance Keypoint Detector for Colored Point Clouds
Content-Based Image Retrieval System
This work generates 2D and 3D landmark labels from videos with only two or three uncalibrated, handheld cameras moving in the wild. NeurIPS 2022.
Code for "Learning a Descriptor-Specific 3D Keypoint Detector" and "Learning to detect good 3d keypoints" -ICCV 2015, IJCV 2018
A CUDA implementation of SIFT
an implement for CenterNet by keras and tensorflow
Swap face between two photos.
Feature Tracking and testing of various keypoint detector/descriptor combinations, keypoint matching using Brute Force and FLANN approach.
This is SRHandNet demo source code written in python3
Facial keypoints detection using 15 landmark points on human face
No description provided.
Code for FashionAI KeyPoint Detection Challenge
human pose estimation based on pose tensorflow
A set of from-scratch MATLAB scripts for detecting Harris corners and edges
PyTorch data loader that crops persons (with their body landmarks) from COCO dataset.
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.
Object detection
A simple and minimal posenet inference in python
Keypoint Tracking and Matching in Autonomous Vehicles to measure TTC between consecutive frames of the KITTI Dataset
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.
3D object tracking using keypoint detection and feature matching, lidar point cloud data, and image classification using YOLO deep learning model.
Keypoint-matching (AKAZE method) using OpenCV library
Estimating trajectory using RGB-D images
No description provided.