Computer Vision
Showing 36 of 599 projects
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.
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 PyTorch adaptation of Lucid for visualizing and interpreting neural networks through feature visualization.
A curated list of awesome Torch tutorials, projects, libraries, and communities for deep learning.
A curated list of deep learning resources for video-text retrieval, including papers, implementations, and datasets.
A free Google Colab-based toolbox with Jupyter notebooks and GUI for applying deep learning to microscopy data without coding expertise.
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.
ROS-based framework and Raspberry Pi image for controlling PX4-powered drones, enabling easy autonomous flight development.
A toolkit and dataset for autonomous driving research, including trajectory prediction, 3D LiDAR detection, scene parsing, and video inpainting.
A whole-slide foundation model for digital pathology, pre-trained on real-world data to analyze tissue slides at tile and slide levels.
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 video-language understanding framework that treats video narration as vocabulary and videos as long documents for efficient analysis.
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 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 comprehensive image processing library for Julia, providing tools for loading, manipulating, and analyzing images.
A web application that uses a CNN model to recognize handwritten Chinese characters from an online drawing canvas.
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.
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.
Delphi and Free Pascal bindings for OpenCV 2.4.13, enabling computer vision development in Object Pascal.
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.
A curated collection of robotics and computer vision datasets for research and development.
A fast C++ GPU implementation of Convolutional Neural Networks with multi-GPU support.
A real-time visual odometry pipeline using stereo event-based cameras, leveraging Time Surfaces for direct geometric mapping and tracking.
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