Thank you for your work. Here's a brief description of our tool.
JoliGEN is an integrated framework for training custom generative AI image-to-image models
Main Features:
JoliGEN implements both GAN and Diffusion models for unpaired and paired image to image translation tasks, including domain and style adaptation with conservation of semantics such as image and object classes, masks, ...
JoliGEN generative AI capabilities are targeted at real world applications such as Controled Image Generation, Augmented Reality, Dataset Smart Augmentation and object insertion, Synthetic to Real transforms.
All features:
SoTA image to image translation
Semantic consistency: conservation of labels of many types: bounding boxes, masks, classes.
GAN data augmentation mechanisms: APA, discriminator noise injection, standard image augmentation, online augmentation through sampling around bounding boxes
Thank you for your work. Here's a brief description of our tool.
JoliGEN is an integrated framework for training custom generative AI image-to-image models
Main Features:
JoliGEN implements both GAN and Diffusion models for unpaired and paired image to image translation tasks, including domain and style adaptation with conservation of semantics such as image and object classes, masks, ...
JoliGEN generative AI capabilities are targeted at real world applications such as Controled Image Generation, Augmented Reality, Dataset Smart Augmentation and object insertion, Synthetic to Real transforms.
All features: