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A comprehensive collection of AI-powered tools, techniques, and resources for building advanced data-driven applications.
A high-performance face recognition library for developers built on PaddlePaddle and PyTorch.
A flexible, high-performance 3D simulator for Embodied AI research
An open-source tool for labeling images and training computer vision models using a variety of popular detection models.
A visual tracking library based on PyTorch for computer vision and machine learning applications.
An open-source deep learning-based tool for automatic colorization of grayscale images.
A fast and simple framework for building neural data processing pipelines using Python.
An open machine learning course that covers a wide range of topics including computer vision, natural language processing, and reinforcement learning.
Real-time dynamic scene rendering using 4D Gaussian Splatting
A 3D computer vision framework for 3D reconstruction, camera tracking, and photogrammetry.
Catalyst is an accelerated deep learning R&D library for Python that supports a variety of AI and machine learning use cases.
An automation black-box testing framework based on image recognition for developers.
A PyTorch implementation of the FCOS one-stage object detection model for computer vision tasks.
A comprehensive library for hand pose estimation and tracking, useful for human-computer interaction projects.
A comprehensive resource for industrial image anomaly/defect detection papers and datasets.
A Python library that provides superfast AI decision-making and intelligent multi-modal data processing.
Effortless AI-assisted data labeling with support from YOLO, Segment Anything (SAM, SAM2), and MobileSAM.
A personal GitHub page for a computer vision and deep learning researcher.
A curated list of the latest AI breakthroughs in 2022 with explanatory videos, articles, and code.
A sparsity-aware deep learning inference runtime for CPUs, optimized for performance and efficiency.
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