Yaxing Wang

Yaxing Wang

PhD Candidate at Computer Vision Center

CVC UAB ZZU

Latest News

1 paper is accepted by NIPS2018, Montréal, CANADA.

1 paper is accepted by ECCV2018, Munich, Germany.

Attended the international conference CVPR 2018, Salt Lake City, US.

1 paper is accepted by CVPR2018, Salt Lake City, US.

Attended the international conference ICLR 2017, Toulon, France.

1 paper is accepted at a workshop NIPS 2016, Barcelona, Spain.

Conferences

Memory Replay GANs: learning to generate images from new categories without forgetting

Authors:Chenshen Wu, Luis Herranz, Xialei Liu, Yaxing Wang, Joost van de Weijer, Bogdan Raducanu

NIPS2018

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Transferring GANs: generating images from limited data

Authors:Yaxing Wang, Chenshen Wu, Luis Herranz, Joost van de Weijer, Abel Gonzalez-Garcia, Bogdan Raducanu

ECCV2018

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Mix and match networks: encoder-decoder alignment for zero-pair image translation

Authors: Yaxing Wang, Joost van de Weijer, Luis Herranz

International Conference on Computer Vision and Pattern Recognition (CVPR), 2018

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Ensembles of generative adversarial networks

Authors:Yaxing Wang, Lichao Zhang, Joost van de Weijer

NIPS 2016 Workshop on Adversarial Training, 2016

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Journals

Coming Soon!

Projects

M2CR

Multimodal Multilingual Continuous Representation for Human Language Understanding

Organizators: Joost van de Weiger, Loïc Barrault, Yoshua Bengio

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Experience

Support researcher - Computer Vision Center (Sep 2015 - Now)

Collaborate with the Learning and Machine Perception (LAMP) groups at different research projects.

Hands-on DL with MatConvNet - Hands-on DL (12. 2015 - 1. 2016)

Collaborate with researchers in CVC

Candidate of PHD - Universitat Autònoma de Barcelona (Sep 2015 - Sep 2019)

PhD scholarship.

Bio

I completed M.Sc. degrees in Signal Processing from the ZhengZhou University (ZZU). Currently, I am pursuing the Ph.D. degree under the supervision of Dr. Joost van de Weijer starting in 2015. I have worked on a wide variety of projects including images for Encoder-decoder, Transfer Learning, Domain Adaptation, Lifelong Learning.