activity
20202024
most citedLearning to dance: A graph convolutional adversarial network to generate realistic dance motions from audio

90 citations · 90 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Empowering Sign Language Communication: Integrating Sentiment and Semantics for Facial Expression Synthesis

Rafael Azevedo, Thiago Coutinho, João Ferreira +2

Translating written sentences from oral languages to a sequence of manual and non-manual gestures plays a crucial role in building a more inclusive society for deaf and hard-of-hea…

cs.CV2021

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…

cs.CV2021

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…

cs.GR2020★ 90 cited

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…

cs.CV2020

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…