Research & Education

Awesome-holistic-3d is a valuable open-source resource for researchers and academics focused on holistic 3D reconstruction in computer vision. This GitHub repository compiles a comprehensive list of relevant papers, datasets, and code, categorized by scene-level and object-level reconstruction. It includes references to tutorials, workshops, and a wide array of research papers spanning from 2009 to 2020. The resource details various datasets with information on the number of scenes, rooms, frames, and annotated structures, making it an essential reference for anyone working on or studying 3D reconstruction techniques.

tf-image-segmentation is an open-source image segmentation framework built upon Tensorflow and the TF-Slim library. Its core purpose is to streamline the process of converting various image segmentation datasets, including general, medical, and other types, into a unified and easy-to-use .tfrecords format for training. The framework includes a robust training routine that supports on-the-fly data augmentation, such as scaling and color distortion, ensuring effective model training. It also provides functionalities for evaluating model accuracy using common metrics like Mean IOU, Mean pixel accuracy, and Pixel accuracy. The framework offers pre-trained model files and definitions for models like FCN-32s, FCN-16s, and FCN-8s, initialized with weights from Image Classification models like VGG, making it a comprehensive solution for researchers and developers working on image segmentation tasks.

Tiny Differentiable Simulator is a header-only C++ and CUDA physics library designed for reinforcement learning and robotics applications. It boasts zero dependencies, making it a lightweight and efficient solution for developers. The library implements various rigid-body dynamics algorithms, including forward and inverse dynamics, alongside contact models based on impulse-level LCP and force-based nonlinear spring-dampers. It also includes actuator models for motors, servos, and Series-Elastic Actuator (SEA) dynamics. The entire codebase is templatized, supporting automatic differentiation scalar types like CppAD, Stan Math fvar, and ceres::Jet, as well as regular float/double precision and fixed-point integer math for cross-platform deterministic computation. It can run thousands of simulations in parallel on a single RTX 2080 CUDA GPU at 50 frames per second and offers OpenGL 3+ and MeshCat visualizers.

awesome-gan-for-medical-imaging is a curated, open-source list of Generative Adversarial Network (GAN) resources specifically tailored for medical imaging applications. Inspired by other 'awesome-*' initiatives, this repository on GitHub provides a comprehensive collection of research papers and code related to GANs in medical contexts. It covers diverse topics such as low-dose CT denoising, medical image segmentation, detection, synthesis, reconstruction, classification, and registration. Researchers can leverage this resource to explore the latest advancements and find relevant studies for their work in medical image analysis and AI development.

awesome-3D-gaussian-splatting is an open-source, curated collection of resources dedicated to 3D Gaussian Splatting (3DGS) and related technologies. This GitHub repository serves as a central hub for researchers, developers, and enthusiasts to explore papers, implementations, viewers, and learning materials. It aims to keep pace with the rapid advancements in 3DGS, offering a comprehensive database of academic papers, various community and official implementations across different programming languages, and support for popular game engines like Unity and Unreal. Additionally, it lists numerous viewers, including web-based, desktop, and VR options, alongside essential tools and utilities for data processing and development. The repository also provides extensive learning resources, including blog posts, talks, and video tutorials, making it an invaluable resource for anyone looking to understand or contribute to the 3DGS domain.

Awesome-3D-Object-Detection-for-Autonomous-Driving is a GitHub repository that accompanies a comprehensive survey paper titled "3D Object Detection for Autonomous Driving: A Comprehensive Survey (IJCV 2023)". This resource is designed to help researchers and engineers stay updated on the latest advancements in 3D object detection techniques for autonomous driving systems. The repository categorizes methods into LiDAR-based, Camera-based, Multi-Modal, Temporal, and Label-Efficient 3D Object Detection, as well as their application in Driving Systems. It provides detailed overviews of various approaches within each category, including point-based, grid-based, anchor-based, and fusion techniques. The content is structured to offer a chronological overview and includes links to relevant papers, making it an essential reference for anyone working in this specialized domain.

Vocabulary is a mobile application designed to elevate word power by introducing users to rare, beautiful, and evocative English words. Unlike typical vocabulary tools, it focuses on advanced learners and native speakers, providing curated collections of poetic and uncommon words. Each entry includes real audio pronunciation, word origins and etymology, and contextual examples to show natural usage. The app offers daily practice, personalized learning paths, and customization options, allowing users to save words, activate reminders, and practice regularly. It also features widgets for passive learning and gamified practice with quizzes to make learning engaging and effective.

Blarma is a mobile application designed to facilitate vocabulary acquisition and language learning through a scientifically proven, four-step method. It leverages visual and audio training, pairing new words with images to trigger dual coding for intuitive understanding. The app places words into AI-personalized sentences and stories, promoting contextual learning similar to real-life language acquisition. Blarma incorporates a smart spaced repetition algorithm to manage the 'forgetting curve,' ensuring long-term retention of vocabulary. Users can engage in unlimited practice drills for pronunciation, writing, and listening, transforming passive knowledge into active language skills. It supports 14 languages and is available on iOS and Android.

awesome-deep-rl is a comprehensive, curated list of resources for Deep Reinforcement Learning. This open-source repository serves as a central hub for researchers and practitioners to discover libraries, benchmark results, environments, competitions, and educational materials like books and tutorials. It covers a wide array of topics, from foundational algorithms and historical timelines to advanced frameworks and simulation platforms, making it an invaluable reference for anyone involved in the field of Deep Reinforcement Learning. The resource is continuously updated, reflecting the dynamic nature of AI research.

Acceleread is a powerful mobile application designed to significantly improve reading speed and comprehension through science-backed techniques. It functions as a "Duolingo for Speed Reading," providing effective exercises and personalized training plans that can boost reading skills in as little as two weeks. The app focuses on both speed and retention, ensuring users not only read faster but also understand and remember more. It is ideal for individuals looking to enhance their reading efficiency, offering an intuitive interface and progress tracking to monitor improvements. Users have reported significant boosts in reading speed and comprehension, making it a valuable tool for anyone aiming to learn faster and retain more information.

AI News for Kids, also known as 6seven, is a unique daily news platform designed specifically for children aged 8 to 15. It leverages an AI named Nova to rewrite complex science and technology news stories into language that is easily understandable and engaging for young minds. The platform aims to not only inform kids about the latest advancements but also to cultivate critical thinking skills by encouraging them to ask deeper questions about the technology shaping their future. With a strong emphasis on privacy, 6seven operates without accounts, tracking, or ads, storing all activity locally on the device. It offers interactive features like short story cards ("Sparks"), deeper article dives, and daily challenges, available in multiple languages, making it an invaluable resource for parents and educators seeking to introduce children to the world of AI and tech in a safe and accessible way.

awesome-embedded-rust is a comprehensive, curated list of resources specifically designed for embedded and low-level development using the Rust programming language. This project is maintained by the Rust Embedded Resources team and serves as a central hub for developers. It features an extensive collection of useful crates, including peripheral access crates for various microcontrollers like Microchip, Nordic, NXP, Raspberry Pi, and STMicroelectronics, as well as HAL implementation and architecture support crates. The list also provides information on real-time operating systems (RTOS) like Drone OS, FreeRTOS.rs, and Tock, alongside a wide array of development tools such as `svd2rust` for generating Rust structs from SVD files, `cargo-flash` for binary downloads, and the `Knurling Tools` suite for building, debugging, and testing embedded Rust systems. Additionally, it offers a rich selection of free and paid books, blogs, and training materials, covering topics from introductory embedded Rust to advanced DSP on Cortex-M microcontrollers.

Awesome-GUI-Agent is a meticulously curated list of papers, projects, and resources specifically focused on multi-modal Graphical User Interface (GUI) agents. This open-source repository serves as a valuable hub for researchers and developers aiming to build advanced digital assistants capable of interacting with computer screens. It categorizes resources into key areas such as Datasets/Benchmarks, Models/Agents, Surveys, and Projects, making it easy to navigate the vast landscape of GUI agent research. The project is actively maintained and encourages contributions, ensuring its relevance and comprehensiveness. It also features an 'Awesome-Paper-Agent' to automatically format arXiv links, streamlining the process of adding new research to the list. This resource is essential for anyone working on or interested in the development of intelligent agents that can understand and operate graphical user interfaces.

Moonshot Math is a formal reasoning model available as a Hugging Face Space, designed to assist users in solving complex mathematical problems. It functions by taking a user-provided math problem or formal statement and generating a detailed, step-by-step solution in Lean 4 code. This capability makes it a valuable resource for individuals seeking to understand or verify mathematical proofs. The tool leverages advanced AI to reason and prove theorems, offering a unique approach to mathematical problem-solving and exploration. Its focus on formal proofs in Lean 4 distinguishes it as a specialized tool for those involved in advanced mathematics or formal verification.

GoReply is a unique platform designed for businesses focusing on Corporate Social Responsibility (CSR) and Environmental, Social, and Governance (ESG) reporting. It enables employees to engage in skill-based, paid volunteering, where consultation fees are donated to carefully vetted charities. The platform connects professionals from leading organizations with individuals seeking expert advice across various industries like Consulting, Healthcare, Finance, Tech, Marketing, and Retail & Real Estate. GoReply helps companies build sustainability reporting networks by documenting employee contributions to social responsibility, enhancing their CSR and ESG profiles. Users can monetize their expertise, reduce unsolicited contact requests, and contribute to causes they care about, while businesses can track and quantify their social impact.

Codeglf is an online platform dedicated to "code golf" challenges, specifically focusing on Python. It provides a competitive environment where developers can solve programming puzzles with the goal of writing the most concise code possible. The platform emphasizes a "local-first" approach, suggesting robust offline capabilities or a focus on client-side processing for an efficient user experience. Codeglf is an excellent resource for Python developers looking to hone their problem-solving skills, learn new language features, and engage in friendly competition. It fosters a deeper understanding of Python's syntax and capabilities, pushing programmers to write elegant and efficient solutions.

Awesome-Implicit-NeRF-Robotics is a curated repository offering a comprehensive list of research papers, code implementations, and related websites focused on Implicit Representations and Neural Radiance Fields (NeRF) within the Robotics and Reinforcement Learning (RL) domains. This resource is largely based on the survey paper "Neural Fields in Robotics: A Survey." It categorizes papers into key areas such as Object Pose Estimation, SLAM, Manipulation/RL, Object Reconstruction, Physics, and Planning/Navigation, making it an invaluable resource for academics and practitioners exploring these advanced topics. The repository is actively maintained, with regular updates on new research and workshops in the field.

fpn.pytorch offers a pure PyTorch implementation of the Feature Pyramid Network (FPN) for object detection, building upon the properties of a faster R-CNN implementation. This project stands out for its complete conversion of all NumPy implementations to PyTorch, ensuring a consistent and efficient environment. A key feature is its support for training with batch sizes greater than one, achieved by revising all relevant layers including dataloader, RPN, and ROI-pooling. It also leverages a multiple GPU wrapper (nn.DataParallel) for flexible scaling across one or more GPUs. The implementation integrates three pooling methods—ROI pooling, ROI align, and ROI crop—all adapted for multi-image batch training. Benchmarking has been conducted on datasets like PASCAL VOC and COCO, demonstrating its performance.

awesome-humanoid-robot-learning is a comprehensive GitHub repository that compiles academic papers focused on the field of humanoid robot learning. The collection is meticulously organized by the specific tasks the papers address, making it easy for researchers to find relevant work. A key differentiator of this list is its preference for papers that include real robot experiments, providing a practical and applied perspective. Additionally, papers that offer open-sourced code are highlighted with a star, encouraging reproducibility and further development within the community. This resource is invaluable for academics, researchers, and engineers looking to stay updated on the latest advancements and foundational studies in humanoid robotics and AI.

avod is an open-source implementation of the Aggregate View Object Detection (AVOD) network, specifically designed for 3D object detection in autonomous driving scenarios. This repository offers a Python-based solution for researchers and developers to implement and experiment with advanced 3D object detection algorithms. It leverages view aggregation techniques to enhance detection accuracy. The project includes detailed instructions for setting up the environment, installing dependencies, configuring training parameters, and running evaluations on datasets like KITTI. It also provides pre-trained models and scripts for visualizing results, making it a comprehensive resource for those working in the field of autonomous vehicle perception.

F0lkl0r3.dev is a unique digital archive that brings the rich history of computing to life through oral history interviews from the Computer History Museum. This platform enriches these invaluable firsthand accounts with AI-generated context, relevant visuals, and interconnected links, creating a searchable and interlinked map of computing history. It serves as an essential resource for historians, researchers, students, and anyone with a keen interest in the evolution of technology. By making complex historical narratives more accessible and engaging, F0lkl0r3.dev allows users to explore the stories of the pioneers who shaped the digital world, understand the intricate connections between various innovations, and gain deeper insights into the foundational moments of computer science.

DeepRL-Tutorials is an open-source repository offering high-quality implementations of various Deep Reinforcement Learning (DRL) algorithms, primarily written in PyTorch. The project emphasizes readability and understanding, making it an excellent resource for those looking to learn and practice DRL concepts. It includes implementations of algorithms such as DQN, Double DQN, Dueling DQN, Rainbow, A2C, PPO, and more, each accompanied by relevant research papers. The tutorials are presented as IPython Notebooks, providing a structured way to explore and experiment with these advanced AI techniques. It requires Python 3.6, Numpy, Gym, Pytorch 0.4.0, Matplotlib, and OpenCV.

Gaussian Splatting Notes is a free, open-source educational resource offering a comprehensive breakdown of the mathematical formulae behind Gaussian Splatting. This guide, presented as a text version of an explanatory stream, delves into the intricacies of the rasterization process, specifically covering the forward and backward passes. It aims to provide as many details as possible, highlighting core algorithmic concepts and referencing original code snippets to aid understanding. The resource also includes important insights marked with '💡' and clarifies complex topics like 3D covariance reparametrization and 2D Gaussian projection, making it an invaluable aid for those studying this advanced 3D rendering technique.

CalcForAnything is a comprehensive platform offering a vast collection of free online calculators across various domains such as solar & energy, finance, health & fitness, math, home & living, nursing & medical, and AI & technology. Users can access instant and accurate results without the need for sign-up or fees. The platform features a diverse array of tools, from a Solar Panel Payback Calculator and Compound Interest Calculator to a Debt Snowball Calculator and Pet Lifetime Cost Calculator. It aims to provide quick answers for personal and business financial planning, health assessments, and everyday calculations, making complex computations accessible and straightforward for everyone.