Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Arnaud Dapogny"'
Autor:
Charline Grossard, Arnaud Dapogny, David Cohen, Sacha Bernheim, Estelle Juillet, Fanny Hamel, Stéphanie Hun, Jérémy Bourgeois, Hugues Pellerin, Sylvie Serret, Kevin Bailly, Laurence Chaby
Publikováno v:
Molecular Autism, Vol 11, Iss 1, Pp 1-14 (2020)
Abstract Background Computer vision combined with human annotation could offer a novel method for exploring facial expression (FE) dynamics in children with autism spectrum disorder (ASD). Methods We recruited 157 children with typical development (T
Externí odkaz:
https://doaj.org/article/6faadb0f136c4abd9d4202e296140d0f
Autor:
Charline Grossard, Laurence Chaby, Stéphanie Hun, Hugues Pellerin, Jérémy Bourgeois, Arnaud Dapogny, Huaxiong Ding, Sylvie Serret, Pierre Foulon, Mohamed Chetouani, Liming Chen, Kevin Bailly, Ouriel Grynszpan, David Cohen
Publikováno v:
Frontiers in Psychology, Vol 9 (2018)
The production of facial expressions (FEs) is an important skill that allows children to share and adapt emotions with their relatives and peers during social interactions. These skills are impaired in children with Autism Spectrum Disorder. However,
Externí odkaz:
https://doaj.org/article/ad4c4712fe93462dbc4b952cf4344f76
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:3664-3676
Pruning Deep Neural Networks (DNNs) is a prominent field of study in the goal of inference runtime acceleration. In this paper, we introduce a novel data-free pruning protocol RED++. Only requiring a trained neural network, and not specific to DNN ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50b24c19cccf97438f89d364150586fe
https://doi.org/10.1109/tpami.2022.3179616
https://doi.org/10.1109/tpami.2022.3179616
Publikováno v:
2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08adda492610a8438f4df03c539c4315
https://doi.org/10.1109/fg57933.2023.10042577
https://doi.org/10.1109/fg57933.2023.10042577
Publikováno v:
2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c014109e9d66ee00451824a891b738e3
https://doi.org/10.1109/fg57933.2023.10042750
https://doi.org/10.1109/fg57933.2023.10042750
Publikováno v:
IEEE Transactions on Biometrics, Behavior, and Identity Science
IEEE Transactions on Biometrics, Behavior, and Identity Science, IEEE, 2019, pp.1-1. ⟨10.1109/TBIOM.2019.2950032⟩
IEEE Transactions on Biometrics, Behavior, and Identity Science, IEEE, 2019, pp.1-1. ⟨10.1109/TBIOM.2019.2950032⟩
Face alignment consists of aligning a shape model on a face image. It is an active domain in computer vision as it is a preprocessing for a number of face analysis and synthesis applications. Current state-of-the-art methods already perform well on "
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0666dced8f2727a09b27880cab3e133
https://doi.org/10.1109/tbiom.2019.2950032
https://doi.org/10.1109/tbiom.2019.2950032
Facial Expression Recognition (FER) is crucial in many research domains because it enables machines to better understand human behaviours. FER methods face the problems of relatively small datasets and noisy data that don't allow classical networks t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3287dbb503dee78694d6f8a92577a655
Publikováno v:
CVPR
CVPR, Jun 2021, Nashville, United States
CVPR, Jun 2021, Nashville, United States
Deep learning approaches are nowadays ubiquitously used to tackle computer vision tasks such as semantic segmentation, requiring large datasets and substantial computational power. Continual learning for semantic segmentation (CSS) is an emerging tre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::455e808538af4df1c53354b3b0258d71
https://hal.archives-ouvertes.fr/hal-03503831
https://hal.archives-ouvertes.fr/hal-03503831
Autor:
Arnaud Dapogny, Hugues Pellerin, Ouriel Grynszpan, Pierre Foulon, Sylvie Serret, Jérémy Bourgeois, Kevin Bailly, Charline Grossard, David Cohen, Fanny Hamel, Estelle Juillet, Heidy Jean-Marie, Stéphanie Hun
Publikováno v:
Creative Education. 10:2347-2366
Background: Children with autism spectrum disorder (ASD) show impairment in producing facial expressions adapted to social contexts. Several serious games have been computed to help them dealing with facial expression recognition but very few focused
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e1dc59fbc113078892b6c42e1583083
https://doi.org/10.4236/ce.2019.1011167
https://doi.org/10.4236/ce.2019.1011167
Publikováno v:
2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Nov 2020, Buenos Aires, France. pp.153-159, ⟨10.1109/FG47880.2020.00081⟩
FG
2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Nov 2020, Buenos Aires, France. pp.153-159, ⟨10.1109/FG47880.2020.00081⟩
FG
Automatic facial expression recognition (FER) is a challenging computer vision problem that finds a number of applications in human-computer interaction. Most recent FER approaches are deep-learning based and involve the extraction of two types of fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bc4ccc57617ac3da8d487f72863b873
https://hal.archives-ouvertes.fr/hal-03181868
https://hal.archives-ouvertes.fr/hal-03181868