Today's Image & Video Generation: Fastest-Growing Projects — April 14, 2026
This week, the Image & Video Generation space on GitHub saw significant activity around tools that enable users to create high-quality visual content using AI. We observed a trend towards open-source solutions that offer advanced video production capabilities and multimodal foundation models for image understanding. These tools are gaining traction among developers due to their versatility and ability to streamline complex tasks.
OpenMontage, with a growth score of 96.03 and 1,651 stars, is the world's first open-source agentic video production system, allowing users to turn their AI coding assistants into full-fledged video production studios. Its rapid growth can be attributed to its comprehensive feature set, including 11 pipelines, 49 tools, and over 400 agent skills.
JoyAI-Image, boasting a growth score of 72.68 and 1,594 stars, is a unified multimodal foundation model for image understanding, text-to-image generation, and instruction-guided image editing. Its popularity stems from its ability to provide a single platform for various image-related tasks, making it an attractive solution for developers seeking efficiency.
Kimodo, developed by NVIDIA, has a growth score of 43.47 and 1,831 stars. This kinematic motion diffusion model is designed for high-quality human(oid) motion generation, showcasing the growing interest in AI-driven animation tools. Its moderate growth rate can be attributed to its specialized focus on motion generation.
Stirling-image, with a growth score of 41.53 and 681 stars, offers a suite of image processing tools within a single Docker container, allowing users to resize, compress, remove backgrounds, upscale, OCR, and more without relying on cloud services. Its growth is driven by the increasing demand for local AI solutions that prioritize data privacy.
MOSS-VL, part of the OpenMOSS ecosystem, has a growth score of 34.67 and 206 stars. This multimodal model series is dedicated to visual understanding, providing developers with a robust foundation for building image-related applications. Its moderate growth rate reflects its niche focus on visual understanding.
Modly, developed by Lightning Pixel, boasts a growth score of 30.73 and 851 stars. This desktop app generates 3D models from images using local AI, leveraging the power of GPUs to deliver high-quality results. Modly's popularity stems from its ability to tap into the growing demand for locally processed computer vision tasks.
AlayaRenderer, developed by ShandaAI, has a growth score of 25.71 and 560 stars. This generative world renderer is designed specifically for games and virtual worlds, showcasing the increasing interest in AI-native rendering engines. Its moderate growth rate can be attributed to its specialized focus on gaming and virtual reality applications.
Forge-film, developed by F-R-L, boasts a growth score of 15.71 and 405 stars. This multi-model DAG-driven parallel AI film generation engine allows for simultaneous scene generation, offering significant speedup compared to traditional methods. Its moderate growth rate reflects its niche appeal within the filmmaking industry.
Pilipili-AutoVideo, developed by OpenDemon, has a growth score of 10.19 and 159 stars. This fully automated AI video agent enables users to generate complete videos with subtitles using local deployment, showcasing the growing interest in accessible AI-driven content creation tools. Its slow growth rate may be due to its relatively specialized focus on automatic video generation.
Awesome-generative-models, maintained by Jiang Chaokang, has a growth score of 10.15 and 99 stars. This repository provides weekly real-time updates on the latest diffusion generation models across various fields, serving as a valuable resource for developers seeking to stay up-to-date with the rapidly evolving landscape of generative AI models.
OpenMontage, with a growth score of 96.03 and 1,651 stars, is the world's first open-source agentic video production system, allowing users to turn their AI coding assistants into full-fledged video production studios. Its rapid growth can be attributed to its comprehensive feature set, including 11 pipelines, 49 tools, and over 400 agent skills.
JoyAI-Image, boasting a growth score of 72.68 and 1,594 stars, is a unified multimodal foundation model for image understanding, text-to-image generation, and instruction-guided image editing. Its popularity stems from its ability to provide a single platform for various image-related tasks, making it an attractive solution for developers seeking efficiency.
Kimodo, developed by NVIDIA, has a growth score of 43.47 and 1,831 stars. This kinematic motion diffusion model is designed for high-quality human(oid) motion generation, showcasing the growing interest in AI-driven animation tools. Its moderate growth rate can be attributed to its specialized focus on motion generation.
Stirling-image, with a growth score of 41.53 and 681 stars, offers a suite of image processing tools within a single Docker container, allowing users to resize, compress, remove backgrounds, upscale, OCR, and more without relying on cloud services. Its growth is driven by the increasing demand for local AI solutions that prioritize data privacy.
MOSS-VL, part of the OpenMOSS ecosystem, has a growth score of 34.67 and 206 stars. This multimodal model series is dedicated to visual understanding, providing developers with a robust foundation for building image-related applications. Its moderate growth rate reflects its niche focus on visual understanding.
Modly, developed by Lightning Pixel, boasts a growth score of 30.73 and 851 stars. This desktop app generates 3D models from images using local AI, leveraging the power of GPUs to deliver high-quality results. Modly's popularity stems from its ability to tap into the growing demand for locally processed computer vision tasks.
AlayaRenderer, developed by ShandaAI, has a growth score of 25.71 and 560 stars. This generative world renderer is designed specifically for games and virtual worlds, showcasing the increasing interest in AI-native rendering engines. Its moderate growth rate can be attributed to its specialized focus on gaming and virtual reality applications.
Forge-film, developed by F-R-L, boasts a growth score of 15.71 and 405 stars. This multi-model DAG-driven parallel AI film generation engine allows for simultaneous scene generation, offering significant speedup compared to traditional methods. Its moderate growth rate reflects its niche appeal within the filmmaking industry.
Pilipili-AutoVideo, developed by OpenDemon, has a growth score of 10.19 and 159 stars. This fully automated AI video agent enables users to generate complete videos with subtitles using local deployment, showcasing the growing interest in accessible AI-driven content creation tools. Its slow growth rate may be due to its relatively specialized focus on automatic video generation.
Awesome-generative-models, maintained by Jiang Chaokang, has a growth score of 10.15 and 99 stars. This repository provides weekly real-time updates on the latest diffusion generation models across various fields, serving as a valuable resource for developers seeking to stay up-to-date with the rapidly evolving landscape of generative AI models.