CVPR 2017 – seqamlab

We are excited to have three CVPR 2017 main conference papers accepted [1, 2, 3], as well as one workshop paper [4] :

[1] B. Babagholami and V. Pavlovic, “Probabilistic Temporal Subspace Clustering,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition, 2017.
[Bibtex]

@inproceedings{babagholami17cvpr,
added-at = {2017-07-18T17:26:03.000+0200},
author = {Babagholami, Behnam and Pavlovic, Vladimir},
biburl = {https://www.bibsonomy.org/bibtex/2e0a04837c7cd0540d2cd2f0aa442a097/vpavlovic},
booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition},
date-added = {2017-01-17 15:43:46 +0000},
date-modified = {2017-01-17 15:45:08 +0000},
interhash = {92906adf52c283061c4f06eaac54aeca},
intrahash = {e0a04837c7cd0540d2cd2f0aa442a097},
keywords = {cvpr17 myown subspace_clustering},
note = {Under review. 50\% contribution.},
timestamp = {2017-07-18T18:07:19.000+0200},
title = {Probabilistic Temporal Subspace Clustering},
year = 2017
}

[2] R. Walecki, O. Rudovic, V. Pavlovic, B. Schuller, and M. Pantic, “Deep Structured Learning for Facial Expression Intensity Estimation,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition, 2017.
[Bibtex]

@inproceedings{walecki17cvpr,
added-at = {2017-07-18T17:26:03.000+0200},
author = {Walecki, Robert and Rudovic, Ognjen and Pavlovic, Vladimir and Schuller, Bjorn and Pantic, Maja},
biburl = {https://www.bibsonomy.org/bibtex/2fd5d11a30fb9f63aa76cfe46783b9bd8/vpavlovic},
booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition},
date-added = {2017-01-17 15:41:28 +0000},
date-modified = {2017-01-17 15:43:23 +0000},
interhash = {956179029a34e1c71fc4b94fb1a90ee8},
intrahash = {fd5d11a30fb9f63aa76cfe46783b9bd8},
keywords = {cvpr17 deep_learning emotion_modeling expression_intensity_estimation myown ordinal_models},
timestamp = {2017-07-22T21:33:47.000+0200},
title = {Deep Structured Learning for Facial Expression Intensity Estimation},
year = 2017
}

[3] L. Sheng, J. Cai, T. Cham, V. Pavlovic, and K. N. Ngan, “A Generative Model for Depth-based Robust 3D Facial Pose Tracking,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition, 2017.
[Bibtex]

@inproceedings{sheng17cvpr,
added-at = {2017-07-18T17:26:03.000+0200},
author = {Sheng, Lu and Cai, Jianfei and Cham, Tat-Jen and Pavlovic, Vladimir and Ngan, King Ngi},
biburl = {https://www.bibsonomy.org/bibtex/2e18c6335e20344d4a11bceb8ec657b57/vpavlovic},
booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition},
date-added = {2017-01-17 15:45:33 +0000},
date-modified = {2017-01-17 15:46:47 +0000},
interhash = {112c6e22dda03c3d485b79595d210af1},
intrahash = {e18c6335e20344d4a11bceb8ec657b57},
keywords = {cvpr17 depth_camera face_modeling face_tracking myown},
note = {Under review. 25\% contribution.},
timestamp = {2017-07-18T18:07:32.000+0200},
title = {A Generative Model for Depth-based Robust 3D Facial Pose Tracking},
year = 2017
}

[4] H. Pham and V. Pavlovic, “Speech-driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach,” in IEEE Int’l Conf. Computer Vision and Pattern Recognition – Workshop on Deep Affective Learning and Context Modeling, 2017.
[Bibtex]

@inproceedings{pham17cvpr,
added-at = {2017-07-18T17:26:03.000+0200},
author = {Pham, Hai and Pavlovic, Vladimir},
biburl = {https://www.bibsonomy.org/bibtex/2e6c72a93e19dd9fe1270b6d559534637/vpavlovic},
booktitle = {IEEE Int'l Conf. Computer Vision and Pattern Recognition - Workshop on Deep Affective Learning and Context Modeling},
interhash = {538627e583e79fae93dd8af09fcdc7eb},
intrahash = {e6c72a93e19dd9fe1270b6d559534637},
keywords = {deep_learning emotion_modeling face_animation myown speech_analysis},
owner = {vladimir},
timestamp = {2017-07-18T18:07:32.000+0200},
title = {Speech-driven 3D Facial Animation with Implicit Emotional Awareness: A Deep Learning Approach},
year = 2017
}

Go to our Research page to find out more.

Congratulations to all!

Leave a Reply Cancel reply