Hamed Pirsiavash

Associate Professor
Department of Computer Science
University of California, Davis

Office: Kemper Hall 3061
Email: hpirsiav AT ucdavis DOT edu

Curriculum Vitae

Google Scholar

Semantic Scholar

I am an associate professor at UC Davis studying computer vision and machine learning. Prior to this, I was an associate professor at UMBC and a postdoctoral research associate with Antonio Torralba at Massachusetts Institute of Technology (MIT). I graduated with a PhD in computer science from the University of California Irvine where I was advised by Deva Ramanan and co-advised by Ramesh Jain. I obtained my M.Sc. in electrical engineering at Sharif University of Technology in Tehran, Iran (map).

Community service:

Associate Editor for IEEE TPAMI, IEEE TNNLS, IET Computer Vision

Area chair for ECCV 2024, ICLR 2024, NeurIPS 2023, ICCV 2023, CVPR 2023, 2020,2018, 2017, ICPR 2022, 2020

Senior PC for AAAI 2023, 2018, IJCAI 2020, 2019

Students:

Ajinkya Tejankar, PhD

Donghee Lee, MSc

Kossar Pourahmadi, PhD

Navaneet Kadur, PhD

Parsa Nooralinejad, PhD

Soroush Abbasi Koohpayegani, PhD

Alumni:

Vipin Pillai, PhD (now at Amazon)

Akshayvarun Subramanya, PhD (now at Apple)

Aniruddha Saha, PhD (now postdoc at University of Mayland)

Ananth Vinjimoor, MSc (now at Amazon Alexa)

Erfan Noury, MSc (now at Apple)

Essam Sleiman, Undergraduate (now at Harvard University)

Koninika Patil, MSc (now at Amazon)

Kshipra Kode, MSc (Co-advised by Nilanjan Banerjee) (now at Meta)

Maryam Esmaeilkhanian, MSc (now at Capital One)

Saeed Damadi, MSc (now PhD student at UMBC Department of Math)

Selected Publications

	NOLA: Networks as Linear Ccombinatotion of Low Rank Random Basis Soroush Abbasi Koohpayegani, K L Navaneet, Parsa Nooralinejad, Soheil Kolouri, Hamed Pirsiavashequal contribution International Conference on Learning Representations (ICLR) 2024.* [PDF] [Code]
	Compact3D: Compressing Gaussian Splat Radiance Field Models with Vector Quantization KL Navaneet, Kossar Pourahmadi Meibodi, Soroush Abbasi Koohpayegani, Hamed Pirsiavash equal contribution arXiv 2023.* [PDF] [Code]
	SimA: Simple Softmax-free Attention for Vision Transformers Soroush Abbasi Koohpayegani, Hamed Pirsiavash IEEE CVF Winter Conference on Applications of Computer Vision (WACV) 2024. [PDF] [Code]
	GeNIe: Generative Hard Negative Images Through Diffusion Soroush Abbasi Koohpayegani, Anuj Singh, K L Navaneet, Hadi Jamali-Rad, Hamed Pirsiavash equal contribution arXiv 2024.* [PDF] [Code]
	PRANC: Pseudo RAndom Networks for Compacting deep models Parsa Nooralinejad, Ali Abbasi, Soroush Abbasi Koohpayegani, Kossar Pourahmadi Meibodi, Rana Muhammad Shahroz Khan, Soheil Kolouri, Hamed Pirsiavashequal contribution International Conference on Computer Vision (ICCV) 2023. [PDF] [Supplementary] [Code]
	A Cookbook of Self-Supervised Learning Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Gregoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum arXiv 2023. [PDF]
	Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning Ajinkya Tejankar, Maziar Sanjabi, Qifan Wang, Sinong Wang, Hamed Firooz, Hamed Pirsiavash, Liang Tan International Conference on Computer Vision and Pattern Recognition (CVPR) 2023. [PDF] [Code]
	Adaptive Inverse Transform Sampling For Efficient Vision Transformers Mohsen Fayyaz, Soroush Abbasi Koohpayegani, Farnoush Rezaei Jafari, Sunando Sengupta, Hamid Reza Vaezi Joze, Eric Sommerlade, Hamed Pirsiavash, Juergen Gallequal contribution European Conference on Computer Vision (ECCV), 2022 (Oral presentation). [PDF] [Supplementary] [Poster] [Video] [Code]
	Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning K L Navaneet, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Kossar Pourahmadi Meibodi, Akshayvarun Subramanya, Hamed Pirsiavashequal contribution European Conference on Computer Vision (ECCV), 2022. [PDF] [Supplementary] [Poster] [Video] [Slides] [Code]
	Can we train vision and language zero-shot classification models without syntax? Ajinkya Tejankar, Bichen Wu , Saining Xie , Madian Khabsa , Hamed Pirsiavash , Hamed Firooz In NeurIPS SSL Theory and Practice Workshop, 2022 [PDF]
	Backdoor Attacks on Vision Transformers Akshayvarun Subramanya, Aniruddha Saha, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash arXiv 2022. [PDF] [Code]
	A Simple Approach to Adversarial Robustness in Few-shot Image Classification Akshayvarun Subramanya, Hamed Pirsiavash ECCV 2022 Workshop on Adversarial Robustness in the Real World [PDF] [Code]
	A Simple Baseline for Low-Budget Active Learning Kossar Pourahmadi, Parsa Nooralinejad, Hamed Pirsiavash arXiv 2021. [PDF] [Code]
	Backdoor Attacks on Self-Supervised Learning Aniruddha Saha, Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Hamed Pirsiavash International Conference on Computer Vision and Pattern Recognition (CVPR) 2022 (Oral presentation). [PDF] [Code]
	Consistent Explanations by Contrastive Learning Vipin Pillai, Soroush Abbasi Koohpayegani, Ashley Ouligian, Dennis Fong, Hamed Pirsiavash International Conference on Computer Vision and Pattern Recognition (CVPR) 2022. [PDF] [Code]
	SimReg: Regression as a Simple Yet Effective Tool for Self-supervised Knowledge Distillation KL Navaneet, Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash British Machine Vision Conference (BMVC) 2021. [PDF] [Code]
	Mean Shift for Self-Supervised Learning Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavashequal contribution International Conference on Computer Vision (ICCV) 2021 (Oral presentation).* [PDF] [Project page] [Code]
	ISD: Self-Supervised Learning by Iterative Similarity Distillation Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Vipin Pillai, Paolo Favaro, Hamed Pirsiavash equal contribution International Conference on Computer Vision (ICCV) 2021.* [PDF] [Project page] [Code]
	Explainable Models with Consistent Interpretations Vipin Pillai, Hamed Pirsiavash 35th AAAI Conference on Artificial Intelligence (AAAI) 2021. [PDF] [Code]
	CompRess: Self-Supervised Learning by Compressing Representations Soroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavashequal contribution Neural Information Processing Systems (NeurIPS) 2020.* [PDF] [Project page] [Code]
	COOT: Cooperative Hierarchical Transformer for Video-Text Representation Learning Simon Ging, Mohammadreza Zolfaghari, Hamed Pirsiavash, Thomas Broxequal contribution Neural Information Processing Systems (NeurIPS) 2020.* [PDF] [Code]
	Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs Soheil Kolouri, Aniruddha Saha, Hamed Pirsiavash†, Heiko Hoffmann† * and †: equal contribution International Conference on Computer Vision and Pattern Recognition (CVPR) 2020 (oral). [PDF] [Code and dataset of models]
	Role of Spatial Context in Adversarial Robustness for Object Detection Aniruddha Saha, Akshayvarun Subramanya, Koninika Patil, Hamed Pirsiavashequal contribution CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision, 2020.* [PDF] [Code]
	Hidden-Trigger Backdoor Attacks Aniruddha Saha, Akshayvarun Subramanya, Hamed Pirsiavash 34th AAAI Conference on Artificial Intelligence (AAAI) 2020 (oral). [PDF] [Code]
	Fooling Network Interpretation in Image Classification Akshayvarun Subramanya, Vipin Pillai, Hamed Pirsiavash equal contribution International Conference on Computer Vision (ICCV) 2019.* [PDF] [Code]
	Boosting Self-Supervised Learning via Knowledge Transfer Mehdi Noroozi, Ananth Vinjimoor, Paolo Favaro, Hamed Pirsiavash International Conference on Computer Vision and Pattern Recognition (CVPR) 2018. [PDF]
	Canonical correlation analysis of brain prefrontal activity measured by functional near infra-red spectroscopy (fNIRS) during a moral judgment task Hadis Dashtestani, Rachel Zaragoza, Hamed Pirsiavash, Kristine M. Knutson, Riley Kermanian, Joy Cui, J. Douglas Harrison Jr., Milton Halem, Amir Gandjbakhche Behavioural Brain Research 2018. [PDF]
	Cross-Modal Scene Networks Yusuf Aytar, Lluís Castrejón, Carl Vondrick, Hamed Pirsiavash, Antonio Torralba equal contribution IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 2018.* [PDF] [Project page]
	Representation Learning by Learning to Count Mehdi Noroozi, Hamed Pirsiavash, Paolo Favaro International Conference on Computer Vision (ICCV) 2017 (oral). [PDF]
	Weakly Supervised Cascaded Convolutional Networks Ali Diba, Vivek Sharma, Ali Pazandeh, Hamed Pirsiavash, Luc Van Gool International Conference on Computer Vision and Pattern Recognition (CVPR) 2017. [PDF]
	Automated Detection of Substance Use-Related Social Media Posts Based on Image and Text Analysis Arpita Roy, Anamika Rupa, Hamed Pirsiavash, Shimei Pan IEEE International Conference on Tools for Artificial Intelligence (ICTAI), 2017. (Best Student Paper Award) [PDF]
	Generating Videos with Scene Dynamics Carl Vondrick, Hamed Pirsiavash, Antonio Torralba Neural Information Processing Systems (NeurIPS), 2016. [PDF] [Project page] [Code] Media coverage: NBC News, Scientific American, New Scientist, MIT News
	Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks Arsalan Mousavian, Hamed Pirsiavash, Jana Kosecka International Conference on 3DVision (3DV), 2016. [PDF]
	Anticipating Visual Representations From Unlabeled Video Carl Vondrick, Hamed Pirsiavash, Antonio Torralba International Conference on Computer Vision and Pattern Recognition (CVPR) 2016 (spotlight). [PDF] [Project page] Media coverage: Forbes, Wired, PopSci, CNN, NPR, Associated Press, Late Show with Stephen Colbert, MIT News
	Learning Aligned Cross-Modal Representations from Weakly Aligned Data Lluís Castrejón, Yusuf Aytar, Carl Vondrick, Hamed Pirsiavash, Antonio Torralba International Conference on Computer Vision and Pattern Recognition (CVPR) 2016. [PDF] [Project page] [Demo]
	Predicting Motivations of Actions by Leveraging Text Carl Vondrick, Deniz Oktay, Hamed Pirsiavash, Antonio Torralba International Conference on Computer Vision and Pattern Recognition (CVPR) 2016. [PDF] [Data]
	DeepCAMP: Deep Convolutional Action & Attribute Mid-Level Patterns Ali Diba, Ali Mohammad Pazandeh, Hamed Pirsiavash, Luc Van Gool International Conference on Computer Vision and Pattern Recognition (CVPR) 2016. [PDF]
	Visualizing Object Detection Features Carl Vondrick, Aditya Khosla, Hamed Pirsiavash, Tomasz Malisiewicz, Antonio Torralba International Journal of Computer Vision (IJCV) 2016. [PDF] [Project page]
	Learning Visual Biases from Human Imagination Carl Vondrick, Hamed Pirsiavash, Aude Oliva, Antonio Torralba Neural Information Processing Systems (NeurIPS), 2015. [PDF] [Project page] Media coverage: Technology Review
	Assessing the Quality of Actions Hamed Pirsiavash, Carl Vondrick, Antonio Torralba European Conference on Computer Vision (ECCV), 2014. [PDF] [Code + Dataset]
	Parsing Videos of Actions with Segmental Grammars Hamed Pirsiavash, Deva Ramanan International Conference on Computer Vision and Pattern Recognition (CVPR) 2014 (oral). [PDF] [Slides PPT (80MB)] Media coverage: NBC News , WIRED-UK , GIGAOM , ScienceDaily , Technology Review , MIT News
	Are All Training Examples Equally Valuable? Agata Lapedriza, Hamed Pirsiavash, Zoya Bylinskii, Antonio Torralba arXiv 2014. [PDF]
	Parsing IKEA Objects: Fine Pose Estimation Joseph Lim, Hamed Pirsiavash, Antonio Torralba International Conference on Computer Vision (ICCV) 2013. [PDF] [Data]
	Detecting Activities of Daily Living in First-person Camera Views Hamed Pirsiavash, Deva Ramanan International Conference on Computer Vision and Pattern Recognition (CVPR) 2012 (oral). [PDF] [Slides PPT (53MB)] [Poster PDF] [Code + Dataset]
	Steerable Part Models Hamed Pirsiavash, Deva Ramanan International Conference on Computer Vision and Pattern Recognition (CVPR) 2012. [PDF] [Slides PPT] [Poster PDF]
	Globally-Optimal Greedy Algorithms for Tracking a Variable Number of Objects Hamed Pirsiavash, Deva Ramanan, Charless Fowlkes International Conference on Computer Vision and Pattern Recognition (CVPR) 2011. [PDF] [Code] [Slides (PPT)] [Slides (PDF)]
	A Large-scale Benchmark Dataset for Event Recognition in Surveillance Video Sangmin Oh et al. International Conference on Computer Vision and Pattern Recognition (CVPR) 2011. [PDF] [Project page]
	TalkMiner: A Lecture Webcast Search Engine John Adcock, Matthew Cooper, Laurent Denoue, Hamed Pirsiavash, Lawrence Rowe ACM Multimedia 2010. [PDF] [www.talkminer.com]
	Bilinear Classifiers for Visual Recognition Hamed Pirsiavash, Deva Ramanan, Charless Fowlkes Neural Information Processing Systems (NeurIPS 2009) (spotlight). [PDF] [Slides PPT] [slides PDF] [Poster PDF]
	Opti-Acoustic Stereo Imaging: On System Calibration and 3-D Target Reconstruction Shahriar Negahdaripour, Hicham Sekkati, Hamed Pirsiavash, IEEE Transactions on Image Processing, Vol 18, Issue 6, Jun 2009, PP: 1203-1214. [PDF]
	Towards Environment-to-Environment (E2E) Multimedia Communication Systems Vivek Singh, Hamed Pirsiavash, Ish Rishabh, Ramesh Jain Multimedia Tools and Applications Journal, Springer Netherlands, Vol 44, Num 3, pp 361-388, May 2009. [PDF]
	Opti-Acoustic Stereo Imaging, System Calibration and 3-D Reconstruction Shahriar Negahdaripour, Hicham Sekkati, Hamed Pirsiavash Workshops of CVPR 2007 - Beyond Multiview Geometry. (Best Paper Award) [PDF]
Please check out the list of older publications.

Hamed Pirsiavash

Community service:

Students:

Alumni:

Selected Publications

Please check out the list of older publications.