Computer Vision
Showing 36 of 253 projects
A pure Rust library for encoding, decoding, and processing images in many common formats.
A simple Go package providing basic image processing functions like resize, rotate, crop, and color adjustments.
Efficient image captioning code in Torch, using a CNN-RNN model to generate captions for images, optimized for GPU training.
A TensorFlow implementation of neural style transfer that transforms images by applying artistic styles from one image to another.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A privacy protection tool that adds imperceptible pixel-level changes to photos to prevent unauthorized facial recognition.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
A fast, flexible C++ standalone library for machine learning with high-performance defaults and total internal modifiability.
A curated collection of papers, code, and resources for domain adaptation in machine learning.
A toolbox for calibrating multi-camera, visual-inertial, and rolling shutter sensor systems in robotics.
Pre-built CPU-only OpenCV packages for Python, providing easy installation via pip without manual compilation.
A fully convolutional neural network for real-time instance segmentation, achieving high speed and accuracy on COCO.
An open-source library for building massively scalable machine learning pipelines on Apache Spark.
A Python library for image augmentation in machine learning, offering a stochastic pipeline approach with fine-grained control over operations.
A hands-on beginner's guide to machine learning and image classification using Caffe and DIGITS with neural networks.
A curated list of awesome Generative Adversarial Network (GAN) applications and demonstrations across various domains.
A PyTorch library providing GPU-accelerated tools for 3D deep learning, including differentiable rendering and geometric operations.
A Swift framework for GPU-accelerated image and video processing on iOS, macOS, and Linux.
A general-purpose tensor library for parallel computing across CPUs, GPUs, and hardware accelerators.
An engine-agnostic deep learning framework for Java developers, providing a high-level API for model training and inference.
A curated collection of academic papers covering all aspects of face analysis, including detection, recognition, alignment, generation, and anti-spoofing.
A collection of infrastructure and tools for research in neural network interpretability and visualization.
A modular container build system providing the latest AI/ML packages for NVIDIA Jetson and JetPack-L4T.
A PyTorch-based research platform implementing state-of-the-art single object tracking algorithms like SiamRPN and SiamMask.
A collection of convenience functions to simplify common image processing tasks with OpenCV and Python.
A comprehensive .NET framework for machine learning, computer vision, statistics, and scientific computing.
An optimization-based multi-sensor state estimator for accurate self-localization in drones, cars, and AR/VR applications.
A 3D point cloud and mesh processing software for comparing, editing, and analyzing large-scale 3D data.
Official PyTorch implementation of HRNet for human pose estimation, maintaining high-resolution representations through parallel multi-scale fusions.
OpenCV bindings for Node.js enabling real-time computer vision applications in JavaScript.
A curated list of papers, software, and resources for 3D reconstruction from images, covering SLAM, SfM, and MVS.
A large-scale dataset of images with object segmentation, bounding boxes, and visual relationship annotations.
A curated list of papers, datasets, and code for 3D point cloud analysis research, covering classification, segmentation, detection, and more.
A Python package for evaluating and comparing odometry and SLAM algorithm trajectories with support for multiple formats and metrics.
A collection of parallel image processing algorithms implemented in pure Go.
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