Shanghang Zhang

Former Collaborator

Group:

Signal and Image Processing Group (SIPG)

Office:

7.10

Position:

PhD Student

Email:

shzhang.pku@gmail.com

FCT:

J6494590g0xs

ORCID:

0000-0003-4047-3526

No projects found

No projects found

[1] Atabak Dehban, ShanghangZhang, Nino Cauli, Lorenzo Jamone, José Santos-Victor "Learning Deep Features for Robotic Inference from Physical Interactions", IEEE Transactions on Cognitive and Developmental Systems, 2022

No publications found for author "cap-shanghangzhang"

No publications found for author "cap-shanghangzhang"

[1] Han Zhao, ShanghangZhang, W. Guanhang, João Paulo Costeira, Jose M. F. Moura, Geoffrey J. Gordon "Adversarial Multiple Source Domain Adaptation", Proc. of 32nd Conference on Neural Information Processing Systems (NeurIPS), Montreal, Canada, 2018
[2] ShanghangZhang, X. Shen, Z. Lin, R. Mech, João Paulo Costeira, Jose M. F. Moura "Learning to Understand Image Blur", accepted, CVPR 2018 - IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, USA, 2018
[3] ShanghangZhang, G. Wu, João Paulo Costeira, J. M. F. Moura "Fcn-rlstm: Deep spatio-temporal neural networks for vehicle counting in city cameras", Proc. of ICCV 2017 - IEEE International Conference on Computer Vision, Venice, Italy, 2017
[4] ShanghangZhang, W. Guanhang, João Paulo Costeira, J. F. Moura "Understanding Traffic Density from Large-Scale Web Camera Data", Proc. of CVPR 2017 - IEEE Conference on Computer Vision and Pattern Recognition, Hawaii, USA, 2017 - PDF
[1] ShanghangZhang "Deep Understanding of Urban Mobility from Cityscape Webcams", Ph.D. Thesis, within the IST-CMU Joint Doctoral Initiative, May, 2018

No publications found for author "cap-shanghangzhang"

No publications found for author "cap-shanghangzhang"

No publications found for author "cap-shanghangzhang"

No publications found for author "cap-shanghangzhang"

[1] João Paulo Costeira, ShanghangZhang "Deep learning methods for estimating density and/or flow of objects, and related methods and software", US patent US10733876B2 Sep,, 2020

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