Amir Rahimi

PhD student, ANU

amir.rahimi [AT]


I am a PhD student in the College of Engineering and Computer Science at the Australian National University, advised by Prof. Richard Hartley. I received my bachelor's and master's degrees from the University of Tehran. My research interests lie in the fields of Computer Vision and Machine Learning. Specifically, I work on problems with limited data/supervision, deep neural network confidence calibration, and inference in probabilistic graphical models. I am also interested in meta-learning and deep invertible networks.

Recent Publications

(Google Scholar Profile)

indicates equal contribution.

Few-shot Weakly-Supervised Object Detection via Directional Statistics

Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley

Arxiv preprint, 2021

Calibration of neural networks using splines

Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley

International Conference on Learning Representation, (ICLR 2021), Virtual Conference (formerly Vienna, Austria).

Post-hoc Calibration of Neural Networks

Amir Rahimi, Kartik Gupta, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley

Arxiv preprint, 2020

Pairwise similarity knowledge transfer for weakly supervised object localization

Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard Hartley, Byron Boots

European Conference on Computer Vision, (ECCV 2020), Virtual Conference (formerly Glasgow, Scotland).

Intra order-preserving functions for calibration of multi-class neural networks

Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley, Byron Boots

34th Conference on Neural Information Processing Systems (NeurIPS 2020), Virtual Conference (formerly Vancouver, Canada).

Learning to find common objects across few image collections

Amirreza Shaban, Amir Rahimi, Shray Bansal, Stephen Gould, Byron Boots, Richard Hartley

Proceedings of the IEEE/CVF International Conference on Computer Vision, (ICCV 2019), Seoul, Korea.