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Reenacting facial images is an important task that can find numerousapplications. We proposed IFaceUV, a fully differentiable pipeline thatproperly combines 2D and 3D information to conduct the facial reenactment task.The three-dimensional morphable face models (3DMMs) and corresponding UV mapsare utilized to intuitively control facial motions and textures, respectively.Two-dimensional techniques based on 2D image warping is further required tocompensate for missing components of the 3DMMs such as backgrounds, ear, hairand etc. In our pipeline, we first extract 3DMM parameters and corresponding UVmaps from source and target images. Then, initial UV maps are refined by the UVmap refinement network and it is rendered to the image with the motionmanipulated 3DMM parameters. In parallel, we warp the source image according tothe 2D flow field obtained from the 2D warping network. Rendered and warpedimages are combined in the final editing network to generate the finalreenactment image. Additionally, we tested our model for the audio-drivenfacial reenactment task. Extensive qualitative and quantitative experimentsillustrate the remarkable performance of our method compared to otherstate-of-the-art methods.

IFaceUV: Intuitive Motion Facial Image Generation by Identity Preservation via UV map