Research & Education

Cap is an open-source screen recording tool designed to be a lightweight, powerful, and cross-platform alternative to services like Loom. It enables users to quickly record their screens and share the content with ease. The tool focuses on providing a seamless experience for capturing visual information, making it suitable for various use cases from tutorials to quick demonstrations. Its open-source nature suggests a community-driven development and potentially greater transparency and customization options for users. Cap aims to simplify the process of creating and distributing screen recordings.

AI Undetect is a freemium undetectable AI tool designed to rewrite and reword AI-generated content, enabling it to bypass various AI detectors. It integrates with leading AI detection interfaces like GPTZero, Copyleaks, and Turnitin, providing users with comprehensive AI detection results. The tool features a self-developed "Undetectable AI Humanizer" large model, trained on a 1B tokens corpus, to ensure high-quality, human-like text. It supports over 20 languages and offers different rewriting styles, including manual and an Auto-Perfect mode for premium users. AI Undetect caters to content creators, students, and digital marketers, helping them maintain authenticity and originality in their work.

Knowmail serves as a dedicated resource for email marketers, offering a wealth of information to improve their strategies. The platform provides expert tips, comprehensive guides, and practical advice covering various aspects of email marketing, from implementing data-driven strategies and optimizing deliverability to crafting engaging email copy and understanding cost factors. It aims to equip both seasoned marketers and beginners with the knowledge and tools needed to excel in the dynamic field of email marketing, ultimately helping them engage audiences, increase conversions, and achieve measurable success.

Grove HR offers a comprehensive resource hub for businesses looking to automate and enhance their human resources processes. The platform provides free guides and insights on critical HR functions, including employee data management, recruitment strategies, attendance tracking, time-off management, onboarding procedures, and performance monitoring. It aims to streamline HR operations by offering valuable content on topics like spotting fake resumes, HR compliance for remote workforces, and leveraging AI tools in HR. Grove HR serves as a knowledge base for HR professionals seeking to optimize their workflows and stay updated on industry best practices.

MIRNet is an advanced AI tool designed for real image restoration and enhancement, leveraging enriched features to deliver state-of-the-art results across various image processing tasks. Its novel architecture maintains spatially-precise high-resolution representations while integrating strong contextual information from low-resolution representations. The core of MIRNet is a multi-scale residual block that incorporates parallel multi-resolution convolution streams for feature extraction, information exchange across these streams, and spatial and channel attention mechanisms for capturing contextual details. This allows for attention-based multi-scale feature aggregation, combining contextual information from multiple scales while preserving high-resolution spatial details. MIRNet excels in image denoising, super-resolution, and image enhancement, as demonstrated by extensive experiments on five real image benchmark datasets.

DeepSurv implements a deep learning generalization of the Cox proportional hazards model using Theano and Lasagne. This approach offers an advantage over traditional Cox regression by adaptively learning covariates, removing the need for their a priori selection. The tool is versatile and can be applied in numerous survival analysis applications. A notable medical application, `recommend_treatment`, is provided, which offers treatment recommendations for patient observations. DeepSurv is open-source and provides clear instructions for installation, dependency management, running experiments with Docker, and training/evaluating networks, making it accessible for technical users in research and development.

motion-diffusion-model is an open-source PyTorch implementation of the "Human Motion Diffusion Model" paper, designed for generating and editing human motion sequences. The tool boasts significant speed improvements, now running 40X faster with a 50-diffusion-step model and optimized CLIP calling. It supports various tasks including text-to-motion, action-to-motion, and unconstrained motion synthesis. Users can generate motions from text prompts or actions, render SMPL meshes, and perform motion editing such as in-between and upper-body modifications. The project also integrates DiP for ultra-fast text-to-motion and offers features like DistilBERT text encoder support and dataset caching for faster loading.

DeepLabCut is an open-source toolbox designed for state-of-the-art markerless pose estimation across various animals and humans. It leverages deep learning to track user-defined features, making it highly versatile and applicable to a wide range of behaviors and species. The tool provides a user-friendly GUI and API, integrating advanced models and frameworks while offering sensible defaults for life scientists. It supports both single and multi-animal pose estimation, identification, and tracking. DeepLabCut is actively maintained, offering continuous improvements, including faster performance variants, real-time capabilities, and a recent backend migration to PyTorch for enhanced flexibility and easier installation. Comprehensive documentation, online courses, and a model zoo are available to assist users.

Finscale AI is an open-source platform dedicated to financial data residency, operating within the Open Constitution AI network. It functions as a research and development lab, providing AI processors to its network constituents. The platform is built upon the Open Constitution licensing framework, emphasizing the development of digital commons infrastructure. Finscale aims to support the secure and localized management of financial data, leveraging AI to enhance its capabilities for various financial applications and research within its ecosystem.

DiscoFaceGAN is a TensorFlow-based implementation for disentangled and controllable face image generation, as presented in a CVPR 2020 Oral paper. This tool allows for the creation of virtual people's faces with precise control over identity, expression, pose, and illumination. It achieves this through 3D imitative-contrastive learning, embedding 3D priors into adversarial learning to imitate the image formation of a 3D face deformation and rendering process. A key feature is its factor disentanglement, ensuring that changing one factor (e.g., expression) does not affect others. The tool also supports reference-based generation, real image pose manipulation, lighting editing, and expression transfer, making it valuable for researchers and developers working with facial image synthesis and manipulation.

OBBDetection is an open-source oriented object detection library built upon MMdetection v2.2, designed for researchers and developers working with object detection tasks. It inherits all features from MMdetection, ensuring a robust and familiar environment. The library supports multiple frameworks and implements various oriented object detectors like RoI Transformer and Gliding Vertex. A key feature is its flexible representation of oriented boxes, accommodating Horizontal Bounding Boxes (HBB), Oriented Bounding Boxes (OBB), and 4-point boxes (POLY). It leverages BboxToolkit for oriented bounding box operations and includes a model zoo with benchmarks for supported methods and backbones. The project is released under the Apache 2.0 license.

RBT Practice Test offers a comprehensive online platform for individuals preparing for the Registered Behavior Technician (RBT) exam. The tool provides four full-length RBT practice tests, each containing 85 challenging, exam-style questions. Users benefit from detailed answer explanations for every question, which helps in understanding key concepts in applied behavior analysis. This resource is designed to boost confidence and improve readiness for the RBT certification, aiming to help candidates pass on their first attempt. The practice exams simulate the real test environment, making it an effective study aid for aspiring RBTs.

Owlvera SAT Prep is a modern platform designed to help students master the SAT exam through consistent, daily practice. Unlike overwhelming test prep courses, Owlvera focuses on providing five expert-crafted practice questions each day, making studying manageable and helping knowledge stick. The platform offers instant feedback, detailed explanations for each question, and comprehensive performance tracking to reveal strengths and weaknesses. Students can also access strategies to improve timing and accuracy, ensuring they develop the skills needed for success on test day. Owlvera aims to boost SAT scores by combining consistent practice with powerful insights, allowing students to study smarter, not harder, and prepare with confidence.

AcademyHunt is India's leading platform designed to help students discover, compare, and choose the best coaching centers and training institutes across various cities. Users can easily search for academies based on specific criteria such as city, desired course, fee range, student reviews, and preferred learning mode (online, offline, or hybrid). The platform offers a side-by-side comparison feature, allowing students to evaluate up to four academies simultaneously to make an informed decision. Academy owners can also register on the platform to list their courses, manage their profiles, and receive student inquiries, with both free and premium listing plans available. AcademyHunt aims to bring transparency and ease to the process of finding quality education and training in India.

PET (Pattern-Exploiting Training) is an open-source research tool designed for few-shot text classification and natural language inference. It employs a semi-supervised training procedure that reformulates input examples as cloze-style phrases, allowing language models to better understand tasks. The tool, along with its iterative variant iPET, demonstrates significant performance improvements over traditional supervised training and other semi-supervised baselines, even surpassing GPT-3 in some low-resource scenarios while requiring substantially fewer parameters. It supports various training modes including PET, iPET, and supervised training, and offers evaluation methods like unsupervised and priming. Researchers can use PET for 13 different tasks, including SuperGLUE tasks, and can also customize it for their own specific applications by defining DataProcessors and PVPs (Pattern-Verbalizer Pairs).

Facial-Expression-Recognition is an open-source deep learning project built with TensorFlow, designed for real-time facial detection in video streams and subsequent recognition of emotional expressions. The tool leverages trained models that have achieved 65% accuracy on the fer2013 dataset, making it a valuable resource for researchers and developers in the field of computer vision and emotion AI. It is primarily tested on Ubuntu and macOS Sierra, offering a robust solution for these environments. Users can easily run a demo to capture faces via webcam and recognize expressions, or train their own models from scratch by downloading and integrating the fer2013 dataset. The project is dependent on Python (>= 3.3), TensorFlow (>= 1.1.0), and OpenCV, providing a clear pathway for installation and usage.

Face-Pose-Net provides a DCNN model and Python code for robustly estimating 6 degrees of freedom (6DoF) 3D face pose or 11 parameters of a 3x4 projection matrix from unconstrained images. A key differentiator is its ability to perform face alignment without relying on fragile landmark detectors, making it highly effective even with low-resolution, occluded, or near-profile views. The tool integrates with a Face Renderer to create an end-to-end pipeline for facial pose estimation and generating multiple rendered views for alignment and data augmentation. It supports both CPU and GPU for extremely fast pose estimation and offers improved face recognition through better face alignment compared to state-of-the-art landmark detectors.

few-shot-object-detection (FsDet) offers official implementations of few-shot object detection benchmarks, including the ICML 2020 paper "Frustratingly Simple Few-Shot Object Detection." It introduces new benchmarks across PASCAL VOC, COCO, and LVIS datasets, with multiple groups of few-shot training examples and evaluation results for both base and novel classes. The repository provides benchmark results and pre-trained models for a two-stage fine-tuning approach (TFA), where the detector is first trained on abundant base classes and then fine-tuned on a small balanced training set. FsDet is modular, allowing for easy integration of custom datasets and models, serving as a general framework for future research in few-shot object detection.

AI Plagiarism Checker by Plagiarismcheck.org is an advanced AI content detector designed to identify AI-generated text quickly and accurately. It helps users, including students, teachers, SEO experts, and recruiters, ensure the originality and authenticity of written content. The tool utilizes cutting-edge AI technology to analyze text for AI traces, including creativity/predictability ratios and stylistic details, providing a comprehensive report that highlights problematic parts. It boasts 97% accuracy and offers features like downloadable reports and strict confidentiality. Integrations with platforms like Canvas, Moodle, Google Classroom, and a Google Docs Add-on make it versatile for academic and professional workflows. The tool is crucial for maintaining academic integrity, safeguarding SEO strategies, and ensuring genuine communication in recruitment.

PassGAN is an open-source deep learning tool for password guessing, implementing the approach described in the paper "PassGAN: A Deep Learning Approach for Password Guessing." This repository provides a modified TensorFlow implementation of Improved Training of Wasserstein GANs, making it easy to train and sample from the model. It includes a command-line interface for generating password samples and training custom models. A pretrained PassGAN model, trained on the RockYou dataset, is also provided. Users can train their own models using various password leaks and datasets, with instructions for downloading common datasets like the LinkedIn leak. The tool is released under an MIT License, acknowledging the original authors of the PassGAN paper and the underlying WGAN training code.

15Minutes offers a comprehensive library of over 5000 book summaries and analyses, designed for quick consumption. Users can explore detailed plots, reviews, and chapter synopses in concise 15-minute reads. Beyond text summaries, the platform also provides audiobooks and podcasts, catering to diverse learning preferences and enabling on-the-go information absorption. It covers a vast array of genres, from self-help and business to science fiction and history, making it a valuable resource for continuous learning and efficient knowledge acquisition across various subjects. The tool aims to help users quickly grasp key insights from a wide range of literature.

Soft-NMS is an open-source algorithm designed to enhance the accuracy of object detection models. It works by intelligently re-scoring bounding box predictions, providing a more robust alternative to traditional Non-Maximum Suppression (NMS). The tool is integrated with popular object detectors such as R-FCN and Faster-RCNN, allowing users to easily incorporate Soft-NMS into their existing pipelines. It supports both linear and Gaussian weighting schemes, with configurable parameters for fine-tuning. Soft-NMS has demonstrated significant performance improvements in challenges like COCO 2017, where it was adopted by many top-performing submissions. The repository provides code for testing models and includes updated ROI Pooling layers for improved interpolation.

StartPlaying is an online platform designed to streamline the process of finding and organizing tabletop roleplaying game sessions. It connects players with a diverse community of professional game masters (GMs), offering a wide range of games and experiences. The platform simplifies scheduling, payment, and communication, making it easier for both GMs to host and players to join engaging RPG adventures. Whether you're looking for a one-shot or a long-term campaign, StartPlaying aims to provide a seamless experience for all participants in the world of online tabletop gaming.

Hamoye.org is a non-profit organization dedicated to fostering AI research and development within emerging economies. The organization aims to democratize access to AI expertise by providing opportunities for local talent to engage in scientific research. Hamoye leverages a technology platform, Hamoye.com, which is powered by a graph of human knowledge concepts, to support its initiatives. This approach helps individuals in these regions to gain valuable skills and contribute to the global AI landscape, addressing the gap in AI talent and resources.