Pritish Sahu

Pritish Sahu is an in Ph.D. program at the computer science department of Rutgers, the State University of New Jersey. He joined Seqam Lab headed by Dr. Pavlovic in Spring 2018. He obtained his M.S. degree from the Computer Science Department at Rutgers University and B.Tech from National Institute of Technology, Rourkela, India.

His research interest are in Machine Learning and Computer Vision. He is currently working on problems pertaining to transfer learning and the disentanglement of latent features deep learning using deep learning. You can follow my research on my personal websiteLink

CV

Authors:

ALL Sahu

Type:

ALL

2019

• M. Kim, Y. Wang, P. Sahu, and V. Pavlovic, “Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement,” in IEEE International Conference on Computer Vision, ICCV, Seoul, Korea, 2019.
  [BibTeX]

  @InProceedings{kim19iccv,
  author = {Minyoung Kim and Yuting Wang and Pritish Sahu and Vladimir Pavlovic},
  booktitle = {{IEEE} International Conference on Computer Vision, {ICCV}},
  title = {Bayes-Factor-{VAE}: Hierarchical {Bayesian} Deep Auto-Encoder Models for Factor Disentanglement},
  year = {2019},
  address = {Seoul, Korea},
  month = oct,
  date-added = {2019-09-05 20:58:51 +0100},
  date-modified = {2019-09-05 21:00:05 +0100},
  }

• B. Gholami, P. Sahu, M. Kim, and V. Pavlovic, “Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation,” in IEEE International Conference on Computer Vision, ICCV, 6th Workshop on Transferring and Adapting Source Knowledge in Computer Vision, Seoul, Korea, 2019.
  [BibTeX]

  @InProceedings{gholami19iccvws,
  author = {Behnam Gholami and Pritish Sahu and Minyoung Kim and Vladimir Pavlovic},
  booktitle = {{IEEE} International Conference on Computer Vision, {ICCV}, 6th Workshop on Transferring and Adapting Source Knowledge in Computer Vision},
  title = {Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation},
  year = {2019},
  address = {Seoul, Korea},
  month = oct,
  date-added = {2019-09-05 20:54:25 +0100},
  date-modified = {2019-09-05 20:57:09 +0100},
  }

• M. Kim, Y. Wang, P. Sahu, and V. Pavlovic, “Relevance Factor VAE: Learning and Identifying Disentangled Factors,” CoRR, vol. abs/1902.01568, 2019.
  [BibTeX]

  @article{kim19rfvae_arxiv,
  Author = {Minyoung Kim and Yuting Wang and Pritish Sahu and Vladimir Pavlovic},
  Journal = {CoRR},
  Title = {Relevance Factor {VAE:} Learning and Identifying Disentangled Factors},
  Volume = {abs/1902.01568},
  Year = {2019}}

• M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised visual domain adaptation: A deep max-margin Gaussian process approach,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, p. 4380–4390.
  [BibTeX]

  @inproceedings{kim2019ugpda,
  Author = {Kim, Minyoung and Sahu, Pritish and Gholami, Behnam and Pavlovic, Vladimir},
  Booktitle = {Proceedings of the {IEEE} Conference on Computer Vision and Pattern Recognition},
  Pages = {4380--4390},
  Title = {Unsupervised visual domain adaptation: A deep max-margin {Gaussian} process approach},
  Year = {2019}}

• M. Kim, P. Sahu, B. Gholami, and V. Pavlovic, “Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach,” CoRR, vol. abs/1902.08727, 2019.
  [BibTeX]

  @article{kim19ugpda_arxiv,
  Author = {Minyoung Kim and Pritish Sahu and Behnam Gholami and Vladimir Pavlovic},
  Journal = {CoRR},
  Title = {Unsupervised Visual Domain Adaptation: {A} Deep Max-Margin {Gaussian} Process Approach},
  Volume = {abs/1902.08727},
  Year = {2019}}

2018

• B. Gholami, P. Sahu, O. Rudovic, K. Bousmalis, and V. Pavlovic, “Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach,” CoRR, vol. abs/1810.11547, 2018.
  [BibTeX]

  @article{behnam18umtda_arxiv,
  Author = {Behnam Gholami and Pritish Sahu and Ognjen Rudovic and Konstantinos Bousmalis and Vladimir Pavlovic},
  Journal = {CoRR},
  Title = {Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach},
  Volume = {abs/1810.11547},
  Year = {2018}}

2016

• S. Yoon, M. Kapadia, P. Sahu, and V. Pavlovic, “Filling in the Blanks: Reconstructing Microscopic Crowd Motion from Multiple Disparate Noisy Sensors,” in 2016 IEEE Winter Applications of Computer Vision Workshops, WACV 2016 Workshops, 2016, p. 1–9. doi:10.1109/wacvw.2016.7470118
  [BibTeX]

  @InProceedings{yoon16wacvws,
  author = {Sejong Yoon and Mubbasir Kapadia and Pritish Sahu and Vladimir Pavlovic},
  booktitle = {2016 {IEEE} Winter Applications of Computer Vision Workshops, {WACV} 2016 Workshops},
  title = {Filling in the Blanks: Reconstructing Microscopic Crowd Motion from Multiple Disparate Noisy Sensors},
  year = {2016},
  month = mar,
  note = {25\% contribution.},
  pages = {1--9},
  date-added = {2016-02-18 13:43:36 +0000},
  date-modified = {2016-09-11 21:17:46 +0000},
  doi = {10.1109/wacvw.2016.7470118},
  }