  We address the task of in-the-wild human figure synthesis, where the primary
goal is to synthesize a full body given any region in any image. In-the-wild
human figure synthesis has long been a challenging and under-explored task,
where current methods struggle to handle extreme poses, occluding objects, and
complex backgrounds.
  Our main contribution is TriA-GAN, a keypoint-guided GAN that can synthesize
Anyone, Anywhere, in Any given pose. Key to our method is projected GANs
combined with a well-crafted training strategy, where our simple generator
architecture can successfully handle the challenges of in-the-wild full-body
synthesis. We show that TriA-GAN significantly improves over previous
in-the-wild full-body synthesis methods, all while requiring less conditional
information for synthesis (keypoints \vs DensePose). Finally, we show that the
latent space of TriA-GAN is compatible with standard unconditional editing
techniques, enabling text-guided editing of generated human figures.
