Today's Image & Video Generation: Fastest-Growing Projects — June 12, 2026
Today's the Image & Video Generation space, we see a strong trend towards lightweight and efficient solutions that cater to both offline and online use cases. Developers are increasingly looking for robust yet user-friendly tools that can handle various tasks like image generation, editing, and video reconstruction without requiring extensive setup or high computational power.
Starting with bytedance/Lance, this project offers a lightweight native unified multimodal model for handling complex tasks such as image and video understanding, generation, and editing. With over 1,000 stars on GitHub, its rapid growth score of 35.70 indicates significant community interest in leveraging Lance's capabilities for diverse multimedia applications.
techjarves/Local-AI-Image-Generator is a fully self-contained offline AI image generation studio designed specifically for Windows users. It runs Stable Diffusion locally with automatic configuration for both Nvidia and AMD/Intel Arc GPUs, eliminating the need for manual setup or system-wide dependencies. The tool's impressive growth score of 34.38 alongside its growing number of stars suggests that it is becoming a go-to solution for those seeking to experiment with AI image generation without internet connectivity constraints.
nv-tlabs/dvlt provides an official implementation of Déjà View, which leverages Looping Transformers for multi-view 3D reconstruction tasks. Despite having fewer commits in the last month compared to others on this list, its solid growth score of 14.04 and over 300 stars indicate a steady increase in interest among researchers and developers working on advanced image processing techniques.
helloianneo/ian-xiaohei-scenes introduces Xiaohei 2.0 Codex Skill for generating Chinese real-object article illustrations and long-scroll story images. The project's growth score of 7.88, along with its growing number of stars, highlights a niche but growing demand in the Chinese market for AI-driven creative content generation.
The Chaning.G-s-Lrlab repository by Guo-chunyu offers an innovative approach to professional photography post-processing by integrating large language models (LLMs) and neural network-level color grading algorithms. This tool's growth score of 6.17 and steadily increasing stars reflect a growing interest in leveraging AI for more personalized and efficient photo editing workflows.
leeguooooo/chatgpt-imagegen allows users to generate images from the command line using their ChatGPT subscription, eliminating the need for API keys or external gateways. With its growth score of 5.52 and over 150 stars, this tool is gaining traction among developers looking for straightforward integration with AI image generation capabilities.
MSALab-PKU/LoomVideo presents an official implementation aimed at unifying multimodal inputs into video generation and editing processes. Its modest but steady growth score of 5.20 alongside a growing number of stars suggests that it is attracting interest from developers and researchers focused on advanced video synthesis techniques.
Another tool worth mentioning in the background removal segment is lilliancrivaro27064501728/AI-Photo-Background-Remover, an easy-to-use desktop utility for removing photo backgrounds offline with high resolution. Its growth score of 3.92 and over 70 stars indicate that it is becoming a preferred choice among users seeking efficient local solutions.
Similarly, r219950810279/AI-Photo-Background-Remover offers another easy-to-use desktop utility for removing photo backgrounds locally with high resolution. With its growth score of 3.86 and growing number of stars, this tool is also gaining traction among users looking for offline background removal solutions.
Lastly, keshik6/gpic provides the official code for GPIC, a giant permissive image corpus aimed at visual generation tasks. Although it has fewer commits in the last month, its growth score of 3.79 and over 40 stars suggest that developers are increasingly recognizing its value as a resource for large-scale image generation projects.
These tools collectively showcase the diverse range of applications and approaches within the Image & Video Generation domain, from lightweight offline solutions to advanced research implementations focused on specific tasks like multi-view reconstruction or color grading.
Starting with bytedance/Lance, this project offers a lightweight native unified multimodal model for handling complex tasks such as image and video understanding, generation, and editing. With over 1,000 stars on GitHub, its rapid growth score of 35.70 indicates significant community interest in leveraging Lance's capabilities for diverse multimedia applications.
techjarves/Local-AI-Image-Generator is a fully self-contained offline AI image generation studio designed specifically for Windows users. It runs Stable Diffusion locally with automatic configuration for both Nvidia and AMD/Intel Arc GPUs, eliminating the need for manual setup or system-wide dependencies. The tool's impressive growth score of 34.38 alongside its growing number of stars suggests that it is becoming a go-to solution for those seeking to experiment with AI image generation without internet connectivity constraints.
nv-tlabs/dvlt provides an official implementation of Déjà View, which leverages Looping Transformers for multi-view 3D reconstruction tasks. Despite having fewer commits in the last month compared to others on this list, its solid growth score of 14.04 and over 300 stars indicate a steady increase in interest among researchers and developers working on advanced image processing techniques.
helloianneo/ian-xiaohei-scenes introduces Xiaohei 2.0 Codex Skill for generating Chinese real-object article illustrations and long-scroll story images. The project's growth score of 7.88, along with its growing number of stars, highlights a niche but growing demand in the Chinese market for AI-driven creative content generation.
The Chaning.G-s-Lrlab repository by Guo-chunyu offers an innovative approach to professional photography post-processing by integrating large language models (LLMs) and neural network-level color grading algorithms. This tool's growth score of 6.17 and steadily increasing stars reflect a growing interest in leveraging AI for more personalized and efficient photo editing workflows.
leeguooooo/chatgpt-imagegen allows users to generate images from the command line using their ChatGPT subscription, eliminating the need for API keys or external gateways. With its growth score of 5.52 and over 150 stars, this tool is gaining traction among developers looking for straightforward integration with AI image generation capabilities.
MSALab-PKU/LoomVideo presents an official implementation aimed at unifying multimodal inputs into video generation and editing processes. Its modest but steady growth score of 5.20 alongside a growing number of stars suggests that it is attracting interest from developers and researchers focused on advanced video synthesis techniques.
Another tool worth mentioning in the background removal segment is lilliancrivaro27064501728/AI-Photo-Background-Remover, an easy-to-use desktop utility for removing photo backgrounds offline with high resolution. Its growth score of 3.92 and over 70 stars indicate that it is becoming a preferred choice among users seeking efficient local solutions.
Similarly, r219950810279/AI-Photo-Background-Remover offers another easy-to-use desktop utility for removing photo backgrounds locally with high resolution. With its growth score of 3.86 and growing number of stars, this tool is also gaining traction among users looking for offline background removal solutions.
Lastly, keshik6/gpic provides the official code for GPIC, a giant permissive image corpus aimed at visual generation tasks. Although it has fewer commits in the last month, its growth score of 3.79 and over 40 stars suggest that developers are increasingly recognizing its value as a resource for large-scale image generation projects.
These tools collectively showcase the diverse range of applications and approaches within the Image & Video Generation domain, from lightweight offline solutions to advanced research implementations focused on specific tasks like multi-view reconstruction or color grading.