no code implementations • 25 Mar 2021 • Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley
When the novel objects are localized, we utilize them to learn a linear appearance model to detect novel classes in new images.
no code implementations • 20 Mar 2020 • Zhaoshuo Li, Amirreza Shaban, Jean-Gabriel Simard, Dinesh Rabindran, Simon DiMaio, Omid Mohareri
Purpose: We describe a 3D multi-view perception system for the da Vinci surgical system to enable Operating room (OR) scene understanding and context awareness.
1 code implementation • ECCV 2020 • Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard Hartley, Byron Boots
Weakly Supervised Object Localization (WSOL) methods only require image level labels as opposed to expensive bounding box annotations required by fully supervised algorithms.
1 code implementation • NeurIPS 2020 • Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley, Byron Boots
A common approach is to learn a post-hoc calibration function that transforms the output of the original network into calibrated confidence scores while maintaining the network's accuracy.
1 code implementation • CVPR 2020 • Hamid Reza Vaezi Joze, Amirreza Shaban, Michael L. Iuzzolino, Kazuhito Koishida
In late fusion, each modality is processed in a separate unimodal Convolutional Neural Network (CNN) stream and the scores of each modality are fused at the end.
Ranked #2 on
Hand Gesture Recognition
on NVGesture
1 code implementation • ICCV 2019 • Amirreza Shaban, Amir Rahimi, Shray Bansal, Stephen Gould, Byron Boots, Richard Hartley
We model the selection as an energy minimization problem with unary and pairwise potential functions.
2 code implementations • 25 Oct 2018 • Amirreza Shaban, Ching-An Cheng, Nathan Hatch, Byron Boots
Bilevel optimization has been recently revisited for designing and analyzing algorithms in hyperparameter tuning and meta learning tasks.
no code implementations • 31 Oct 2017 • Alexander Lambert, Amirreza Shaban, Amit Raj, Zhen Liu, Byron Boots
We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics.
6 code implementations • 11 Sep 2017 • Amirreza Shaban, Shray Bansal, Zhen Liu, Irfan Essa, Byron Boots
Low-shot learning methods for image classification support learning from sparse data.
no code implementations • 3 Mar 2014 • Mohammadzaman Zamani, Hamid Beigy, Amirreza Shaban
With the increasing volume of data in the world, the best approach for learning from this data is to exploit an online learning algorithm.
no code implementations • 24 Nov 2013 • Amirreza Shaban, Hamid R. Rabiee, Mahyar Najibi
Data coding as a building block of several image processing algorithms has been received great attention recently.
no code implementations • CVPR 2013 • Amirreza Shaban, Hamid R. Rabiee, Mehrdad Farajtabar, Marjan Ghazvininejad
Exploiting the local similarity of a descriptor and its nearby bases, a global measure of association of a descriptor to all the bases is computed.