Computer Vision
Showing 36 of 599 projects
A curated list of academic papers and resources for image and video inpainting techniques.
A comprehensive C++ toolkit for mobile robotics and computer vision research, providing libraries for SLAM, Bayesian filtering, and 3D geometry.
A C++ library for real-time metric-semantic SLAM, building semantically annotated 3D meshes from camera and IMU data.
A web/desktop application for collaborative labeling and annotation of images, text, audio, documents, and other data types.
A PHP library for generating perceptual image hashes to detect similar or duplicate images.
A C library for efficient image processing and analysis, widely used in OCR and computer vision applications.
An unsupervised learning framework for depth and ego-motion estimation from monocular videos using TensorFlow.
A deep learning-based facial detection library for Python with facial landmark extraction.
A pure Python computer vision library based on the book 'Programming Computer Vision with Python'.
A web-based labeling tool for creating semantic segmentation training data from 2D images and 3D point clouds.
A curated collection of datasets for Simultaneous Localization and Mapping (SLAM) research, categorized by topic, platform, and environment.
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A deep learning-based edge detection algorithm using holistically-nested fully convolutional neural networks.
A Python library implementing multiple alpha matting algorithms for extracting foreground objects from images.
A computer vision library for human-computer interaction, focusing on head pose estimation, gaze direction, skin detection, motion tracking, and saliency mapping using CNNs.
An end-to-end deep learning system for reconstructing complete 3D scenes (geometry and semantics) from posed 2D images.
A pure Go implementation that finds optimal image crops for arbitrary aspect ratios using content-aware analysis.
A real-time baseline 3D multi-object tracking system using LiDAR point clouds, combining 3D Kalman filter and Hungarian algorithm.
A smart and easy-to-use image masking and cutout SDK for iOS and iPadOS mobile applications.
A modular C++ library implementing the Iterative Closest Point (ICP) algorithm for aligning 2D and 3D point clouds in robotics and computer vision.
A pure Go library providing a comprehensive set of image processing filters with no external dependencies.
An end-to-end 3D object detection network that uses deep point set networks and Hough voting to directly detect objects in point clouds.
A realtime LiDAR odometry and mapping (LOAM) method for state estimation and mapping using 3D lidar sensors like Velodyne VLP16.
A ROS package for extrinsic calibration between LiDAR and camera sensors using 3D-3D point correspondences.
React Native binding for iOS ARKit, enabling augmented reality app development with 3D components and plane detection.
An open-source, near photo-realistic 3D simulation platform for training and evaluating embodied AI agents.
An open-source computer vision tool that detects, tracks, and counts moving objects from cameras and videos.
TensorFlow implementation of YOLO for real-time object detection using pretrained YOLO_small, YOLO_tiny, and YOLO_face models.
A curated checklist of state-of-the-art research materials (datasets, papers, code) for interaction-aware trajectory prediction.
A deep learning pipeline for 3D object detection from RGB-D data by combining 2D detectors with PointNet-based 3D processing.
An open-source C library with MATLAB interfaces implementing popular computer vision algorithms for image understanding and local feature extraction.
A collection of high-performance GICP-based point cloud registration algorithms with multi-threaded and GPU-accelerated implementations.
A lightweight C++/Python library for 3D data processing, geometry algorithms, and rendering with an easy-to-use API.
A real-time monocular SLAM system for computing camera trajectories and sparse 3D scene reconstruction.
An all-in-one framework for training state-of-the-art computer vision models, covering pretraining, fine-tuning, and distillation.
A general-purpose PyTorch codebase for 3D object detection with state-of-the-art model implementations and multi-dataset support.
An efficient neural network for semantic segmentation of large-scale 3D point clouds using random sampling.
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