Popular GitHub Repositories for Fair Comparison

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!

An open and fair framework for everyone to build AI agents equipped with powerful skills. Launch your agent, improve the world, your wallet, or both!

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)

Fast face detection, pupil/eyes localization and facial landmark points detection library in pure Go.

Facilitating the design, comparison and sharing of deep text matching models.

Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 7 billion with natural language (powered by OpenAI). Follow us on Twitter: https://twitter.com/ossinsight

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.

Integrate deep learning models for image classification | Backbone learning/comparison/magic modification project

ARCH models in Python

Human ChatGPT Comparison Corpus (HC3), Detectors, and more! ?

FAIR Sequence Modeling Toolkit 2

LeGO-LOAM, LIO-SAM, LVI-SAM, FAST-LIO2, Faster-LIO, VoxelMap, R3LIVE, Point-LIO, KISS-ICP, DLO, DLIO, Ada-LIO, PV-LIO, SLAMesh, ImMesh, FAST-LIO-MULTI, M-LOAM, LOCUS, SLICT, MA-LIO, CT-ICP, GenZ-ICP, iG-LIO, SR-LIO application and comparison on Gazebo and real-world datasets. Installation and config files are provided.

[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods

? The experiment tracker for foundation model training

Facilitating the design, comparison and sharing of deep text matching models.

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking

Face recognition SDK Android with 3D passive face liveness detection: face recognition by face matching, face compare, face comparison, face identification, face anti-spoofing, face identity, facial recognition, face representation, face reconstruction, and face liveness detection for IDV