Beijing Zhiyuan Artificial Intelligence Research Institute (BAAI) has launched a new all-round visual generation model OmniGen, which has made a significant breakthrough in the field of image generation. With its unity, simplicity, and cross-task knowledge transfer capabilities, OmniGen can efficiently handle a variety of image generation tasks within a single framework, including image generation, image editing, topic-driven generation, and visual condition generation. It can even complete image removal. Classic computer vision tasks such as noise and edge detection. The editor of Downcodes will explain in detail the powerful functions and convenient operation of OmniGen.
Beijing Zhiyuan Artificial Intelligence Research Institute (BAAI) recently announced the launch of a new all-round visual generation model OmniGen, marking a major breakthrough in the field of image generation. The OmniGen model is known for its unity, simplicity, and cross-task knowledge transfer capabilities. It can handle a variety of image generation tasks within a single framework, including image generation, image editing, topic-driven generation, and visual condition generation. In addition, OmniGen is also able to handle some classic computer vision tasks, such as image denoising and edge detection, by converting these tasks into image generation tasks.
The core advantage of OmniGen lies in its simplified architecture and user-friendly operation. Users can complete complex image generation tasks through simple instructions without additional plug-ins or complex processing steps. This unified format of learning enables OmniGen to effectively transfer knowledge across different tasks, cope with unseen tasks and domains, and demonstrate novel capabilities.
The capabilities of the OmniGen model are not limited to the above, but also include basic image processing capabilities such as denoising and edge extraction. The model's weights and code have been made open source so that users can explore more of OmniGen's capabilities on their own and fine-tune as needed. Zhiyuan Research Institute has constructed a large-scale and diverse unified image generation data set X2I, containing approximately 100 million images, which will be open source in the future to promote the development of the field of general image generation.
Related links:
Paper: https://arxiv.org/pdf/2409.11340
Code: https://github.com/VectorSpaceLab/OmniGen
Demo: https://huggingface.co/spaces/Shitao/OmniGen
All in all, the emergence of the OmniGen model has brought new possibilities to the field of image generation, and its powerful functions and convenient operations will surely promote further development in this field. Open source model weights and codes also provide valuable resources for developers. We look forward to OmniGen bringing innovation and breakthroughs to more application scenarios in the future. The editor of Downcodes will continue to pay attention to the latest progress of this model and bring you more related reports.