90 citations · 90 across the 3 of their papers we have counts for
4 papers
Creating and Reenacting Controllable 3D Humans with Differentiable Rendering
Thiago L. Gomes, Thiago M. Coutinho, Rafael Azevedo +2
This paper proposes a new end-to-end neural rendering architecture to transfer appearance and reenact human actors. Our method leverages a carefully designed graph convolutional ne…
A Shape-Aware Retargeting Approach to Transfer Human Motion and Appearance in Monocular Videos
Thiago L. Gomes, Renato Martins, João Ferreira +3
Transferring human motion and appearance between videos of human actors remains one of the key challenges in Computer Vision. Despite the advances from recent image-to-image transl…
Learning to dance: A graph convolutional adversarial network to generate realistic dance motions from audio
João P. Ferreira, Thiago M. Coutinho, Thiago L. Gomes +4
Synthesizing human motion through learning techniques is becoming an increasingly popular approach to alleviating the requirement of new data capture to produce animations. Learnin…
Do As I Do: Transferring Human Motion and Appearance between Monocular Videos with Spatial and Temporal Constraints
Thiago L. Gomes, Renato Martins, João Ferreira +1
Creating plausible virtual actors from images of real actors remains one of the key challenges in computer vision and computer graphics. Marker-less human motion estimation and sha…