Image Recognition
The research team developed a unified vision system for object recognition and classification, learning from limited examples, image synthesis under text or class limitations, and image modification. Likewise, a unified vision system requires comprehensive visual world comprehension. The MAsked Generative Encoder (MAGE) vision system can locate and classify objects in photos, learn from a few instances, generate images with text or class, alter images, and more. Such a tokenization step can be pre-trained on large image datasets without labels using a self-supervised framework. On large image datasets like ImageNet, it achieves outstanding results with only a few tagged instances thanks to its proficiency in few-shot learning.