{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/unsupervised-depth-estimation-3d-face","title":"Unsupervised Depth Estimation, 3D Face Rotation and Replacement","arxiv_id":"1803.09202","date":"2018-03-25","proceeding":"NeurIPS 2018 12","authors":["Joel Ruben Antony Moniz","Christopher Beckham","Simon Rajotte","Sina Honari","Christopher Pal"],"abstract":"We present an unsupervised approach for learning to estimate three\ndimensional (3D) facial structure from a single image while also predicting 3D\nviewpoint transformations that match a desired pose and facial geometry. We\nachieve this by inferring the depth of facial keypoints of an input image in an\nunsupervised manner, without using any form of ground-truth depth information.\nWe show how it is possible to use these depths as intermediate computations\nwithin a new backpropable loss to predict the parameters of a 3D affine\ntransformation matrix that maps inferred 3D keypoints of an input face to the\ncorresponding 2D keypoints on a desired target facial geometry or pose. Our\nresulting approach, called DepthNets, can therefore be used to infer plausible\n3D transformations from one face pose to another, allowing faces to be\nfrontalized, transformed into 3D models or even warped to another pose and\nfacial geometry. Lastly, we identify certain shortcomings with our formulation,\nand explore adversarial image translation techniques as a post-processing step\nto re-synthesize complete head shots for faces re-targeted to different poses\nor identities.","url_abs":"http://arxiv.org/abs/1803.09202v5","url_pdf":"http://arxiv.org/pdf/1803.09202v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"unsupervised-depth-estimation-3d-face","repo_url":"https://github.com/joelmoniz/DepthNets","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"depth-estimation","task_name":"Depth Estimation"},{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.09202","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}