Search Results for author: Amirreza Shaban

Found 14 papers, 6 papers with code

LiDAR-UDA: Self-ensembling Through Time for Unsupervised LiDAR Domain Adaptation

no code implementations ICCV 2023 Amirreza Shaban, Joonho Lee, Sanghun Jung, Xiangyun Meng, Byron Boots

Existing self-training methods use a model trained on labeled source data to generate pseudo labels for target data and refine the predictions via fine-tuning the network on the pseudo labels.

Pseudo Label Unsupervised Domain Adaptation

CAFA: Class-Aware Feature Alignment for Test-Time Adaptation

no code implementations ICCV 2023 Sanghun Jung, Jungsoo Lee, Nanhee Kim, Amirreza Shaban, Byron Boots, Jaegul Choo

That is, a model does not have a chance to learn test data in a class-discriminative manner, which was feasible in other adaptation tasks (\textit{e. g.,} unsupervised domain adaptation) via supervised losses on the source data.

Unsupervised Domain Adaptation

A Robotic 3D Perception System for Operating Room Environment Awareness

no code implementations20 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.

3D Semantic Segmentation Scene Segmentation +1

Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization

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.

Transfer Learning Weakly-Supervised Object Localization

Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks

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.

MMTM: Multimodal Transfer Module for CNN Fusion

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.

Action Recognition In Videos Hand Gesture Recognition +3

Truncated Back-propagation for Bilevel Optimization

2 code implementations25 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.

Bilevel Optimization Meta-Learning

Deep Forward and Inverse Perceptual Models for Tracking and Prediction

no code implementations31 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.

Image Generation

Cascading Randomized Weighted Majority: A New Online Ensemble Learning Algorithm

no code implementations3 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.

Ensemble Learning

Local Similarities, Global Coding: An Algorithm for Feature Coding and its Applications

no code implementations24 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.

From Local Similarity to Global Coding: An Application to Image Classification

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.

General Classification Image Classification

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