ONNX-compatible LightGlue: Local Feature Matching at Light Speed. Supports TensorRT, OpenVINO
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Updated
Oct 7, 2024 - Python
ONNX-compatible LightGlue: Local Feature Matching at Light Speed. Supports TensorRT, OpenVINO
Homography Decomposition Networks for Planar Object Tracking
Vision-based GNSS-Free Localization for UAVs in the Wild
This is the official repo for the CVPR 2021 IMW paper: "Perceptual Loss for Robust Unsupervised Homography Estimation"
ONNX-compatible DeDoDe 🎶 Detect, Don't Describe - Describe, Don't Detect, for Local Feature Matching. Supports TensorRT 🚀
Implementation of Panorama stitching using ORB feature matching, and RANSAC for homography estimation, and stitching using Image pyramids.
Repository contains applications that can 1. estimate homography matrix and annotate minion images on empty billboards; 2. Estimate Depth using Sum of Squared Distance and Cross Correlation Metrics as well as improve the results using Viterbi Algorithm. Error in Estimated Depth Map is also measured quantitatively against Ground Truth Images.
This repository contains an implementation of panorama stitching, a computer vision technique used to combine multiple images into a seamless panoramic image. The project leverages classical techniques such as feature detection, matching, and RANSAC, along with a deep learning approach using Homography Net and Tensor DLT.
Autopano - Stirching multiple images to form a seamless panorama
Implementation of an homography algorithm for computer vision
Image stitching using Feature Matching and Deep Learning methods.
Finds corner features in multiple images and aligns the images in a mosaic by estimating a homography between corresponding features
Simple exercise for image stitching
Deep learning approaches for estimating homography between images
Stabilo is a Python package for stabilizing video frames or object trajectories using advanced transformation techniques. It supports user-defined masks to exclude specific areas, making it ideal for dynamic scenes with moving objects. Unlike traditional stabilization, it stabilizes content relative to a chosen reference frame.
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