Pirsiavash, Hamed

Globally-optimal greedy algorithms for tracking a variable number of objects

Pirsiavash, H., Ramanan, D., & Fowlkes, C. C. (2011) · CVPR 2011

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 790

Generating Videos with Scene Dynamics

Vondrick, C., Pirsiavash, H., & Torralba, A. (2016) · Maryland Shared Open Access Repository

Generative Adversarial Networks and Image SynthesisHuman Pose and Action Recognition

Cited by 441

Weakly Supervised Cascaded Convolutional Networks

Diba, A., Sharma, V., Pazandeh, A., Pirsiavash, H., & Van Gool, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 287

Parsing IKEA Objects: Fine Pose Estimation

Lim, J. J., Pirsiavash, H., & Torralba, A. (2013) · 2013 IEEE International Conference on Computer Vision

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 249

Learning Aligned Cross-Modal Representations from Weakly Aligned Data

Castrejon, L., Aytar, Y., Vondrick, C., Pirsiavash, H., & Torralba, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 188

A Cookbook of Self-Supervised Learning

Balestriero, R., Ibrahim, M., Sobal, V., Morcos, A., Shekhar, S., Goldstein, T., Bordes, F., Bardes, A., Mialon, G., Tian, Y., et al. (2023) · arXiv

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 182

A collective AI via lifelong learning and sharing at the edge

Soltoggio, A., Ben-Iwhiwhu, E., Braverman, V., Eaton, E., Epstein, B., Ge, Y., Halperin, L., How, J., Itti, L., Jacobs, M. A., et al. (2024) · Nature Machine Intelligence

Domain Adaptation and Few-Shot LearningIoT and Edge/Fog Computing

Cited by 51

Hidden Trigger Backdoor Attacks

Saha, A., Subramanya, A., & Pirsiavash, H. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 13