M. Harandi

发表

Unsupervised Domain Adaptation by Domain Invariant Projection

Brian C. Lovell, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2013, 2013 IEEE International Conference on Computer Vision.

Spatio-temporal covariance descriptors for action and gesture recognition

Brian C. Lovell, Andres Sanin, Conrad Sanderson, 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

Face Recognition from Still Images to Video Sequences: A Local-Feature-Based Framework

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2011, EURASIP J. Image Video Process..

Improved Image Set Classification via Joint Sparse Approximated Nearest Subspaces

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Learning an Invariant Hilbert Space for Domain Adaptation

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Samitha Herath, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Optimal Local Basis: A Reinforcement Learning Approach for Face Recognition

Majid Nili Ahmadabadi, Babak Nadjar Araabi, Mehrtash Tafazzoli Harandi, 2009, International Journal of Computer Vision.

Siamese Networks : A Thing or Two to Know

Mehrtash Harandi, M. Harandi, 2017 .

Supplementary Material : Min-Max Statistical Alignment for Transfer Learning

R. Nock, Basura Fernando, M. Harandi, 2019 .

Supplementary Material for Siamese Networks: The Tale of Two Manifolds

R. Hartley, R. Nock, M. Harandi, 2019 .

Fisher Tensors for Classifying Human Epithelial Cells Fisher Tensors for Classifying Human Epithelial Cells

M. Harandi, B. Lovell, A. Wiliem, 2015 .

Learning Discriminative αβ-Divergences for Positive Definite Matrices 1

M. Harandi, V. Morellas, A. Cherian, 2022 .

Deep Subspace Networks For Few-Shot Learning

Richard Nock, Mehrtash Harandi, Piotr Koniusz, 2019 .

Characterizing Subtle Facial Movements via Riemannian Manifold

M. Pietikäinen, Guoying Zhao, M. Harandi, 2019, ACM Transactions on Multimedia Computing, Communications, and Applications.

Learning to Learn via Gradient Component Corrections

Richard Nock, Mehrtash Harandi, Piotr Koniusz, 2019 .

Coordinate Coding on the Riemannian Manifold of Symmetric Positive-Definite Matrices for Image Classification

M. Harandi, B. Lovell, Mina Basirat, 2016 .

Curvature Generation in Curved Spaces for Few-Shot Learning

M. Harandi, Yunde Jia, Yuwei Wu, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Adaptive Poincaré Point to Set Distance for Few-Shot Classification

M. Harandi, T. Drummond, Pengfei Fang, 2022, AAAI.

Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning

M. Harandi, T. Drummond, Pengfei Fang, 2021, ECCV.

Curved Geometric Networks for Visual Anomaly Recognition

M. Harandi, L. Petersson, Pengfei Fang, 2022, IEEE transactions on neural networks and learning systems.

Improved Object Tracking via Bags of Affine Subspaces

C. Sanderson, M. Harandi, C. McCool, 2014, ArXiv.

Deep Laparoscopic Stereo Matching with Transformers

M. Harandi, T. Drummond, ZongYuan Ge, 2022, MICCAI.

Curvature-Adaptive Meta-Learning for Fast Adaptation to Manifold Data

M. Harandi, Yunde Jia, Yuwei Wu, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Supplementary Material: Non-Linear Stationary Subspace Analysis with Application to Video Classication

M. Salzmann, M. Harandi, B. Lovell, 2012 .

Going deeper into action recognition: A survey

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Samitha Herath, 2016, Image Vis. Comput..

Kernel analysis on Grassmann manifolds for action recognition

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2013, Pattern Recognit. Lett..

Graph-Embedding Discriminant Analysis on Riemannian Manifolds for Visual Recognition

Mehrtash Harandi, Brian C. Lovell, Azadeh Alavi, 2013 .

M2SGD: Learning to Learn Important Weights

Mehrtash Harandi, Gabriela Ferraro, Hanna Suominen, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Adaptive Subspaces for Few-Shot Learning

Mehrtash Harandi, Piotr Koniusz, Christian Simon, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Machine learning applications in computer vision

Mehrtash Harandi, Brian C. Lovell, Javid Taheri, 2012 .

Ensemble Learning for Object Recognition and Tracking

Mehrtash Harandi, Brian C. Lovell, Javid Taheri, 2011 .

Affinity guided Geometric Semi-Supervised Metric Learning pdf

Mehrtash Harandi, Chellu Chandra Sekhar, Ujjal Kr Dutta, 2020, ArXiv.

Executable thematic special issue on pattern recognition techniques for indirect immunofluorescence images analysis

Alessia Saggese, Mario Vento, Mehrtash Harandi, 2016, Pattern Recognition Letters.

Fisher tensors for classifying human epithelial cells

Brian C. Lovell, Arnold Wiliem, Mehrtash Tafazzoli Harandi, 2014, Pattern Recognit..

Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation pdf

Mehrtash Harandi, Xin Wang, Zongyuan Ge, 2020, ArXiv.

Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels

Hongdong Li, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Domain Adaptation by Joint Distribution Invariant Projections

Mehrtash Harandi, Sentao Chen, Xiaona Jin, 2020, IEEE Transactions on Image Processing.

Hyperbolic Geometry in Computer Vision: A Survey

Dinh Q. Phung, Trung-Nghia Le, M. Harandi, 2023, ArXiv.

Learning to Continually Learn Rapidly from Few and Noisy Data

M. Harandi, H. Suominen, Christian J. Walder, 2021, MetaDL@AAAI.

Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation

Dwarikanath Mahapatra, Mehrtash Harandi, Tom Drummond, 2021, ArXiv.

Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model pdf

Nick Barnes, Mehrtash Harandi, Richard Hartley, 2021, ArXiv.

Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning

M. Harandi, L. Petersson, S. Roy, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Combining Multiple Manifold-Valued Descriptors for Improved Object Recognition

Hongdong Li, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2013, 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Implicit Motion Handling for Video Camouflaged Object Detection

M. Harandi, T. Drummond, ZongYuan Ge, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Hierarchical Neural Architecture Search for Deep Stereo Matching pdf

Mehrtash Harandi, Zongyuan Ge, Yiran Zhong, 2020, NeurIPS.

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Nick Barnes, Jing Zhang, Yuchao Dai, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

More about VLAD: A leap from Euclidean to Riemannian manifolds

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Masoud Faraki, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Siamese Networks: The Tale of Two Manifolds

Richard Nock, Mehrtash Harandi, Soumava Kumar Roy, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Directional Space-Time Oriented Gradients for 3D Visual Pattern Analysis

Brian C. Lovell, Mehrtash Tafazzoli Harandi, Adam Postula, 2012, ECCV.

Revisiting Bilinear Pooling: A Coding Perspective

Yunde Jia, Mehrtash Harandi, Yuwei Wu, 2020, AAAI.

Bilinear Attention Networks for Person Retrieval

Lars Petersson, Mehrtash Harandi, Soumava Kumar Roy, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Lars Petersson, Mehrtash Harandi, Soumava Kumar Roy, 2020, Image Vis. Comput..

Learning to Optimize on SPD Manifolds

Yunde Jia, Mehrtash Harandi, Yuwei Wu, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods

Mehrtash Harandi, Richard Hartley, Mathieu Salzmann, 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Joint Dimensionality Reduction and Metric Learning: A Geometric Take

Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Richard I. Hartley, 2017, ICML.

On Modulating the Gradient for Meta-learning

Richard Nock, Mehrtash Harandi, Piotr Koniusz, 2020, ECCV.

A Framework for Shape Analysis via Hilbert Space Embedding

Hongdong Li, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2013, 2013 IEEE International Conference on Computer Vision.

On robust biometric identity verification via sparse encoding of faces: Holistic vs local approaches

Yongkang Wong, Brian C. Lovell, Conrad Sanderson, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices pdf

Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Richard I. Hartley, 2014, ECCV.

Riemannian coding and dictionary learning: Kernels to the rescue

Mehrtash Tafazzoli Harandi, Mathieu Salzmann, M. Salzmann, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Kernel Coding: General Formulation and Special Cases pdf

Mehrtash Tafazzoli Harandi, Mathieu Salzmann, M. Salzmann, 2014, ArXiv.

Bregman Divergences for Infinite Dimensional Covariance Matrices

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Mathieu Salzmann, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices

Hongdong Li, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Sparse Coding and Dictionary Learning for Symmetric Positive Definite Matrices: A Kernel Approach

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2012, ECCV.

Combined Learning of Salient Local Descriptors and Distance Metrics for Image Set Face Verification

Yongkang Wong, Brian C. Lovell, Conrad Sanderson, 2012, 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance.

Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures

Brian C. Lovell, Arnold Wiliem, Conrad Sanderson, 2012, 2012 IEEE Workshop on the Applications of Computer Vision (WACV).

Unsupervised Deep Metric Learning via Orthogonality Based Probabilistic Loss

Mehrtash Harandi, Chellu Chandra Sekhar, Ujjal Kr Dutta, 2020, IEEE Transactions on Artificial Intelligence.

Museum Exhibit Identification Challenge for the Supervised Domain Adaptation and Beyond

Rui Zhang, Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, 2018, ECCV.

Discriminative Non-Linear Stationary Subspace Analysis for Video Classification

Brian C. Lovell, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2013, 2013 IEEE International Conference on Computer Vision.

Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2014, International Journal of Computer Vision.

Museum Exhibit Identification Challenge for Domain Adaptation and Beyond pdf

Rui Zhang, Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, 2018, ArXiv.

Approximate infinite-dimensional Region Covariance Descriptors for image classification

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Masoud Faraki, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Multimorbidity Content-Based Medical Image Retrieval Using Proxies

Benjamin J. Meyer, M. Harandi, T. Drummond, 2022, ArXiv.

When VLAD Met Hilbert

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Mathieu Salzmann, 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Domain Adaptation on the Statistical Manifold

Brian C. Lovell, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Bags of Affine Subspaces for Robust Object Tracking

Conrad Sanderson, Mehrtash Tafazzoli Harandi, Chris McCool, 2014, 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

Expanding the Family of Grassmannian Kernels: An Embedding Perspective

Hongdong Li, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2014, ECCV.

On robust face recognition via sparse coding: the good, the bad and the ugly

Yongkang Wong, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2013, IET Biom..

Material Classification on Symmetric Positive Definite Manifolds

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Masoud Faraki, 2015, 2015 IEEE Winter Conference on Applications of Computer Vision.

Image set classification by symmetric positive semi-definite matrices

Mehrtash Tafazzoli Harandi, Fatih Murat Porikli, Masoud Faraki, 2016, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).

Non-Linear Stationary Subspace Analysis with Application to Video Classification

Brian C. Lovell, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2013, ICML.

Ensemble of furthest subspace pairs for enhanced image set matching

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2011, 2011 18th IEEE International Conference on Image Processing.

Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2011, CVPR 2011.

Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning

Lars Petersson, Mehrtash Harandi, Soumava Kumar Roy, 2021, Computer Vision and Pattern Recognition.

Adaptive Poincaré Point to Set Distance for Few-Shot Classification

Tom Drummond, Pengfei Fang, Mehrtash Harandi, 2021, AAAI.

Set Augmented Triplet Loss for Video Person Re-Identification pdf

Mehrtash Harandi, Pengfei Fang, Pan Ji, 2020, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).

Distribution-Matching Embedding for Visual Domain Adaptation

Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Mahsa Baktash, 2016, J. Mach. Learn. Res..

Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2014, IEEE Transactions on Neural Networks and Learning Systems.

K-tangent spaces on Riemannian manifolds for improved pedestrian detection

Brian C. Lovell, Andres Sanin, Conrad Sanderson, 2014, 2012 19th IEEE International Conference on Image Processing.

Dictionary Learning on Grassmann Manifolds

Mehrtash Harandi, Jochen Trumpf, Mathieu Salzmann, 2016 .

Clustering on Grassmann manifolds via kernel embedding with application to action analysis

Brian C. Lovell, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2012, 2012 19th IEEE International Conference on Image Processing.

Learning from Noisy Labels via Discrepant Collaborative Training

Yan Han, Lars Petersson, Mehrtash Harandi, 2020, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

On robust face recognition via sparse coding: the good, the bad and the ugly pdf

Yongkang Wong, Conrad Sanderson, Mehrtash Tafazzoli Harandi, 2013, IET Biom..

On Robust Biometric Identity Veriﬁcation via Sparse Encoding of Faces: Holistic vs Local Approaches

M. Harandi, Yongkang Wong, C. Sanderson, 2022 .

A Robust Distance Measure for Similarity-Based Classification on the SPD Manifold

Yunde Jia, Mehrtash Harandi, Yuwei Wu, 2020, IEEE Transactions on Neural Networks and Learning Systems.

A Probabilistic approach for Learning Embeddings without Supervision pdf

Mehrtash Harandi, Chellu Chandra Sekhar, Ujjal Kr Dutta, 2019, ArXiv.

Semi-Supervised Domain Adaptation via Asymmetric Joint Distribution Matching

Mehrtash Harandi, Xiaowei Yang, Sentao Chen, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Channel Recurrent Attention Networks for Video Pedestrian Retrieval pdf

Mehrtash Harandi, Pengfei Fang, Pan Ji, 2020, ACCV.

An Input Residual Connection for Simplifying Gated Recurrent Neural Networks

Mehrtash Harandi, Gabriela Ferraro, Hanna Suominen, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Learning Discriminative αβ-divergence for Positive Definite Matrices pdf

Vassilios Morellas, Anoop Cherian, Panagiotis Stanitsas, 2017 .

Optimizing over Radial Kernels on Compact Manifolds

Hongdong Li, Mehrtash Tafazzoli Harandi, Mathieu Salzmann, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.