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Found 6 papers, 0 papers with code
Automatic Detection of Sentimentality from Facial Expressions
To the best of our knowledge this is the first work to address the problem of sentimentality detection.
AFFDEX 2.0: A Real-Time Facial Expression Analysis Toolkit
In this paper we introduce AFFDEX 2. 0 - a toolkit for analyzing facial expressions in the wild, that is, it is intended for users aiming to; a) estimate the 3D head pose, b) detect facial Action Units (AUs), c) recognize basic emotions and 2 new emotional states (sentimentality and confusion), and d) detect high-level expressive metrics like blink and attention.
Choose Settings Carefully: Comparing Action Unit detection at Different Settings Using a Large-Scale Dataset
In this paper, we investigate the impact of some of the commonly used settings for (a) preprocessing face images, and (b) classification and training, on Action Unit (AU) detection performance and complexity.
Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset
In this paper we explore the influence of some frequently used Convolutional Neural Networks (CNNs), training settings, and training set structures, on Action Unit (AU) detection.
TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition
At the heart of our network is a meta-learning approach that learns to compare representations of variable temporal length, that is, either two videos of different length (in the case of few-shot action recognition) or a video and a semantic representation such as word vector (in the case of zero-shot action recognition).
Ranked #7 on
Few Shot Action Recognition
on Kinetics-100
SchiNet: Automatic Estimation of Symptoms of Schizophrenia from Facial Behaviour Analysis
Patients with schizophrenia often display impairments in the expression of emotion and speech and those are observed in their facial behaviour.
