activity
20162024
most citedModeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection

17 citations · 17 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2024

GHOST: Grounded Human Motion Generation with Open Vocabulary Scene-and-Text Contexts

Zoltán Á. Milacski, Koichiro Niinuma, Ryosuke Kawamura +2

The connection between our 3D surroundings and the descriptive language that characterizes them would be well-suited for localizing and generating human motion in context but for o…

cs.CV2024

D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment

Lin Zhang, Linghan Xu, Saman Motamed +2

Unsupervised domain adaptation (UDA) for image classification has made remarkable progress in transferring classification knowledge from a labeled source domain to an unlabeled tar…

cs.CV2021

MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement

Alexander Richard, Michael Zollhoefer, Yandong Wen +2

This paper presents a generic method for generating full facial 3D animation from speech. Existing approaches to audio-driven facial animation exhibit uncanny or static upper face…

cs.CV2021

Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality

Amin Jourabloo, Baris Gecer, Fernando De la Torre +7

Social presence, the feeling of being there with a real person, will fuel the next generation of communication systems driven by digital humans in virtual reality (VR). The best 3D…

cs.CV2017

Discriminative Optimization: Theory and Applications to Computer Vision Problems

Jayakorn Vongkulbhisal, Fernando De la Torre, João P. Costeira

Many computer vision problems are formulated as the optimization of a cost function. This approach faces two main challenges: (i) designing a cost function with a local optimum at…

cs.CV2016★ 17 cited

Modeling Spatial and Temporal Cues for Multi-label Facial Action Unit Detection

Wen-Sheng Chu, Fernando De la Torre, Jeffrey F. Cohn

Facial action units (AUs) are essential to decode human facial expressions. Researchers have focused on training AU detectors with a variety of features and classifiers. However, s…