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Found 9 papers, 1 papers with code
Leveraging The Topological Consistencies of Learning in Deep Neural Networks
Our newly developed practical topological characterization of DNNs allows for an additional set of applications.
Detail Me More: Improving GAN's Photo-Realism of Complex Scenes
Generative models can synthesize photo-realistic images of a single object.
Automatic selection of eye tracking variables in visual categorization in adults and infants
With its tight link to visual attention, eye tracking is a promising method for getting access to the mechanisms of category learning.
Cross-Cultural and Cultural-Specific Production and Perception of Facial Expressions of Emotion in the Wild
Yet, the study of emotion requires knowing which facial expressions are used within and across cultures in the wild, not in controlled lab conditions; but such studies do not exist.
GANimation: Anatomically-aware Facial Animation from a Single Image
Recent advances in Generative Adversarial Networks (GANs) have shown impressive results for task of facial expression synthesis.
Learning Facial Action Units From Web Images With Scalable Weakly Supervised Clustering
We present a scalable weakly supervised clustering approach to learn facial action units (AUs) from large, freely available web images.
Recognition of Action Units in the Wild With Deep Nets and a New Global-Local Loss
Most previous algorithms for the recognition of Action Units (AUs) were trained on a small number of sample images.
EmotioNet Challenge: Recognition of facial expressions of emotion in the wild
The second track tested the algorithms' ability to recognize emotion categories in images of facial expressions.
EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild
Herein, we present a novel computer vision algorithm to annotate a large database of one million images of facial expressions of emotion in the wild (i. e., face images downloaded from the Internet).
