Multimodal machine learning: A survey and taxonomy
T Baltrušaitis, C Ahuja… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Our experience of the world is multimodal-we see objects, hear sounds, feel texture, smell
odors, and taste flavors. Modality refers to the way in which something happens or is …
odors, and taste flavors. Modality refers to the way in which something happens or is …
Survey on rgb, 3d, thermal, and multimodal approaches for facial expression recognition: History, trends, and affect-related applications
CA Corneanu, MO Simón, JF Cohn… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Facial expressions are an important way through which humans interact socially. Building a
system capable of automatically recognizing facial expressions from images and video has …
system capable of automatically recognizing facial expressions from images and video has …
Emotion recognition for multiple context awareness
Understanding emotion in context is a rising hotspot in the computer vision community.
Existing methods lack reliable context semantics to mitigate uncertainty in expressing …
Existing methods lack reliable context semantics to mitigate uncertainty in expressing …
M3er: Multiplicative multimodal emotion recognition using facial, textual, and speech cues
We present M3ER, a learning-based method for emotion recognition from multiple input
modalities. Our approach combines cues from multiple co-occurring modalities (such as …
modalities. Our approach combines cues from multiple co-occurring modalities (such as …
Mart: Masked affective representation learning via masked temporal distribution distillation
Limited training data is a long-standing problem for video emotion analysis (VEA). Existing
works leverage the power of large-scale image datasets for transferring while failing to …
works leverage the power of large-scale image datasets for transferring while failing to …
Deep learning for emotion recognition on small datasets using transfer learning
HW Ng, VD Nguyen, V Vonikakis… - Proceedings of the 2015 …, 2015 - dl.acm.org
This paper presents the techniques employed in our team's submissions to the 2015
Emotion Recognition in the Wild contest, for the sub-challenge of Static Facial Expression …
Emotion Recognition in the Wild contest, for the sub-challenge of Static Facial Expression …
Image based static facial expression recognition with multiple deep network learning
We report our image based static facial expression recognition method for the Emotion
Recognition in the Wild Challenge (EmotiW) 2015. We focus on the sub-challenge of the …
Recognition in the Wild Challenge (EmotiW) 2015. We focus on the sub-challenge of the …
Emonets: Multimodal deep learning approaches for emotion recognition in video
The task of the Emotion Recognition in the Wild (EmotiW) Challenge is to assign one of
seven emotions to short video clips extracted from Hollywood style movies. The videos …
seven emotions to short video clips extracted from Hollywood style movies. The videos …
Video and image based emotion recognition challenges in the wild: Emotiw 2015
The third Emotion Recognition in the Wild (EmotiW) challenge 2015 consists of an audio-
video based emotion and static image based facial expression classification sub …
video based emotion and static image based facial expression classification sub …
Video-based emotion recognition in the wild using deep transfer learning and score fusion
Multimodal recognition of affective states is a difficult problem, unless the recording
conditions are carefully controlled. For recognition “in the wild”, large variances in face pose …
conditions are carefully controlled. For recognition “in the wild”, large variances in face pose …