Computer Vision
Showing 36 of 711 projects
Official PyTorch implementation for joint monocular 3D vehicle detection and tracking from ICCV 2019.
A ROS package for calibrating camera and LiDAR sensors using OpenCV's PnP and Levenberg-Marquardt optimization.
A tiny JavaScript library for applying image processing filters directly in the browser.
A deep learning library for tag estimation and semantic feature vector extraction from illustrations.
A dense visual odometry and SLAM system for RGB-D cameras that estimates camera motion from consecutive depth images.
A PyTorch adaptation of Lucid for visualizing and interpreting neural networks through feature visualization.
Bridge between ROS 2 and OpenCV for real-time computer vision applications.
Bridge between ROS 2 and OpenCV for real-time computer vision applications.
A curated list of awesome Torch tutorials, projects, libraries, and communities for deep learning.
ROS-based framework and Raspberry Pi image for controlling PX4-powered drones, enabling easy autonomous flight development.
A free Google Colab-based toolbox with Jupyter notebooks and GUI for applying deep learning to microscopy data without coding expertise.
A curated list of deep learning resources for video-text retrieval, including papers, implementations, and datasets.
A LiDAR-based tool for constructing static maps by removing dynamic points from point cloud sequences.
A Python package for visualizing and processing 2D/3D point clouds with interactive rendering and parallelized queries.
A ROS-based tool for manually calibrating extrinsic parameters between Livox LiDAR sensors and cameras using board corners.
Build fully-functioning computer vision and object detection models with PyTorch in just 5 lines of code.
A whole-slide foundation model for digital pathology, pre-trained on real-world data to analyze tissue slides at tile and slide levels.
A toolkit and dataset for autonomous driving research, including trajectory prediction, 3D LiDAR detection, scene parsing, and video inpainting.
A convolutional network-based image classifier and feature extractor trained on ImageNet, providing dense feature extraction capabilities.
TensorFlow implementation of GAN-CLS algorithm for generating images from text descriptions using adversarial networks.
A deep learning system that classifies food images into 230 categories and retrieves matching recipes using convolutional neural networks.
A curated collection of open-source machine learning models compatible with Apple's Core ML framework.
A video-language understanding framework that treats video narration as vocabulary and videos as long documents for efficient analysis.
A convolutional neural network model for real-time road-object segmentation from 3D LiDAR point clouds.
A low-cost and accurate SLAM system that fuses Livox lidar with camera data for robust localization and mapping.
A Unity SDK for integrating IBM Watson AI services like speech, language, and vision into games and applications.
A benchmark dataset for long-range (up to 250m) dense depth estimation in autonomous driving, featuring 360° LiDAR ground truth.
A web application that uses a CNN model to recognize handwritten Chinese characters from an online drawing canvas.
A comprehensive image processing library for Julia, providing tools for loading, manipulating, and analyzing images.
Android app that uses your camera to identify objects and translate their names into different languages.
A curated list of popular deep learning models for image classification, segmentation, and detection with key performance metrics.
Delphi and Free Pascal bindings for OpenCV 2.4.13, enabling computer vision development in Object Pascal.
A collection of practical ARKit 2.0 sample projects for iOS developers, featuring drawing, 3D modeling, physics, and face detection.
A U-Net implementation for brain tumor segmentation using the BRATS 2017 dataset with data augmentation and dice loss.
A lightweight encoder-decoder neural network for real-time semantic segmentation on resource-constrained devices.
A sliding window framework for classifying high-resolution whole-slide microscopy and histopathology images using deep neural networks.
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