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Synthesis and Rendering

PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD


Smiling has a psychiatric effect in emotional state and may hold tremendous potential for clinical remediation in psychiatric disorders. A few researchers in image synthesis work on acting on the emotional state of subjects by automatically deforming their faces to synthesize joyful expression. However, to generate these expressions they apply the same deformation for the subjects while each person smiles differently. In this paper, we head towards a personalized synthesis of the joy expression.

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16 September 2019 - 7:40am
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[1] , "PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4639. Accessed: Jul. 04, 2020.
@article{4639-19,
url = {http://sigport.org/4639},
author = { },
publisher = {IEEE SigPort},
title = {PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD},
year = {2019} }
TY - EJOUR
T1 - PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4639
ER -
. (2019). PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD. IEEE SigPort. http://sigport.org/4639
, 2019. PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD. Available at: http://sigport.org/4639.
. (2019). "PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD." Web.
1. . PERSON-SPECIFIC JOY EXPRESSION SYNTHESIS WITH GEOMETRIC METHOD [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4639

CANNYGAN: Edge-PREserving image translation with disentangled features


The image-to-image translation task often associates with the problem of missing texture and edge information. In this paper, we proposed a framework to translate images while preserving more realistic textures and details. To this end, we disentangle the samples into shared content space and domain-specific style domain. Then, according to the blurred outlines and textures in the source domain, we introduce the classic canny edge detection algorithm to encode the boundary and edge information in the content latent space.

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Tianren Wang, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell
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20 September 2019 - 11:30am
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[1] Tianren Wang, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell, "CANNYGAN: Edge-PREserving image translation with disentangled features", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4577. Accessed: Jul. 04, 2020.
@article{4577-19,
url = {http://sigport.org/4577},
author = {Tianren Wang; Teng Zhang; Liangchen Liu; Arnold Wiliem; Brian Lovell },
publisher = {IEEE SigPort},
title = {CANNYGAN: Edge-PREserving image translation with disentangled features},
year = {2019} }
TY - EJOUR
T1 - CANNYGAN: Edge-PREserving image translation with disentangled features
AU - Tianren Wang; Teng Zhang; Liangchen Liu; Arnold Wiliem; Brian Lovell
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4577
ER -
Tianren Wang, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell. (2019). CANNYGAN: Edge-PREserving image translation with disentangled features. IEEE SigPort. http://sigport.org/4577
Tianren Wang, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell, 2019. CANNYGAN: Edge-PREserving image translation with disentangled features. Available at: http://sigport.org/4577.
Tianren Wang, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell. (2019). "CANNYGAN: Edge-PREserving image translation with disentangled features." Web.
1. Tianren Wang, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell. CANNYGAN: Edge-PREserving image translation with disentangled features [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4577