Baktashmotlagh, Mahsa

38 publications

WACV 2025 Feature Space Perturbation: A Panacea to Enhanced Transferability Estimation Prafful Kumar Khoba, Zijian Wang, Chetan Arora, Mahsa Baktashmotlagh

ICML 2025 Improving Out-of-Distribution Detection via Dynamic Covariance Calibration Kaiyu Guo, Zijian Wang, Tan Pan, Brian C. Lovell, Mahsa Baktashmotlagh

ECML-PKDD 2025 Leveraging Gradient Information for Out-of-Domain Performance Estimations Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann

ICLR 2025 MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection Zhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh, Yonggang Zhang, Zi Huang, Yadan Luo

NeurIPS 2025 Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization Tan Pan, Kaiyu Guo, Dongli Xu, Zhaorui Tan, Chen Jiang, Deshu Chen, Xin Guo, Brian C. Lovell, Limei Han, Yuan Cheng, Mahsa Baktashmotlagh

ICCV 2025 Not All Views Are Created Equal: Analyzing Viewpoint Instabilities in Vision Foundation Models Mateusz Michalkiewicz, Sheena Bai, Mahsa Baktashmotlagh, Varun Jampani, Guha Balakrishnan

ICCV 2025 PEFTDiff: Diffusion-Guided Transferability Estimation for Parameter-Efficient Fine-Tuning Prafful Kumar Khoba, Zijian Wang, Chetan Arora, Mahsa Baktashmotlagh

ECML-PKDD 2025 Spectral Distribution Alignment for Enhanced Generalization in Regression Kaiyu Guo, Zijian Wang, Brian C. Lovell, Mahsa Baktashmotlagh

NeurIPS 2024 Color-Oriented Redundancy Reduction in Dataset Distillation Bowen Yuan, Zijian Wang, Mahsa Baktashmotlagh, Yadan Luo, Zi Huang

NeurIPS 2024 DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection Jia Syuen Lim, Zhuoxiao Chen, Mahsa Baktashmotlagh, Zhi Chen, Xin Yu, Zi Huang, Yadan Luo

ECCV 2024 Source-Free Domain-Invariant Performance Prediction Ekaterina Khramtsova, Mahsa Baktashmotlagh, Guido Zuccon, Xi Wang, Mathieu Salzmann

WACV 2024 Towards Domain-Aware Knowledge Distillation for Continual Model Generalization Nikhil Reddy, Mahsa Baktashmotlagh, Chetan Arora

WACV 2023 Center-Aware Adversarial Augmentation for Single Domain Generalization Tianle Chen, Mahsa Baktashmotlagh, Zijian Wang, Mathieu Salzmann

AISTATS 2023 Convolutional Persistence as a Remedy to Neural Model Analysis Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh

ICCV 2023 Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters Mateusz Michalkiewicz, Masoud Faraki, Xiang Yu, Manmohan Chandraker, Mahsa Baktashmotlagh

ICLR 2023 Exploring Active 3D Object Detection from a Generalization Perspective Yadan Luo, Zhuoxiao Chen, Zijian Wang, Xin Yu, Zi Huang, Mahsa Baktashmotlagh

WACV 2023 FFM: Injecting Out-of-Domain Knowledge via Factorized Frequency Modification Zijian Wang, Yadan Luo, Zi Huang, Mahsa Baktashmotlagh

ICCV 2023 How Far Pre-Trained Models Are from Neural Collapse on the Target Dataset Informs Their Transferability Zijian Wang, Yadan Luo, Liang Zheng, Zi Huang, Mahsa Baktashmotlagh

ICCV 2023 KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection Yadan Luo, Zhuoxiao Chen, Zhen Fang, Zheng Zhang, Mahsa Baktashmotlagh, Zi Huang

ICCV 2023 Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-Balanced Pseudo-Labeling Zhuoxiao Chen, Yadan Luo, Zheng Wang, Mahsa Baktashmotlagh, Zi Huang

WACV 2022 Learning to Generate the Unknowns as a Remedy to the Open-Set Domain Shift Mahsa Baktashmotlagh, Tianle Chen, Mathieu Salzmann

ECCV 2022 Master of All: Simultaneous Generalization of Urban-Scene Segmentation to All Adverse Weather Conditions Nikhil Reddy, Abhinav Singhal, Abhishek Kumar, Mahsa Baktashmotlagh, Chetan Arora

WACV 2021 Keypoint-Aligned Embeddings for Image Retrieval and Re-Identification Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh

ICCV 2021 Learning to Diversify for Single Domain Generalization Zijian Wang, Yadan Luo, Ruihong Qiu, Zi Huang, Mahsa Baktashmotlagh

ICLR 2021 Semi-Supervised Keypoint Localization Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh

ECCV 2020 Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas, Mahsa Baktashmotlagh, Anders Eriksson, Eugene Belilovsky

AAAI 2020 Learning from the past: Continual Meta-Learning with Bayesian Graph Neural Networks Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh, Yang Yang

ICML 2020 Progressive Graph Learning for Open-Set Domain Adaptation Yadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh

ICLR 2019 Learning Factorized Representations for Open-Set Domain Adaptation Mahsa Baktashmotlagh, Masoud Faraki, Tom Drummond, Mathieu Salzmann

WACV 2019 Multi-Component Image Translation for Deep Domain Generalization Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh, Sridha Sridharan

AAAI 2017 From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach Sarah M. Erfani, Mahsa Baktashmotlagh, Masud Moshtaghi, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao

JMLR 2016 Distribution-Matching Embedding for Visual Domain Adaptation Mahsa Baktashmotlagh, Mehrtash Harandi, Mathieu Salzmann

IJCAI 2016 Robust Domain Generalisation by Enforcing Distribution Invariance Sarah M. Erfani, Mahsa Baktashmotlagh, Masud Moshtaghi, Vinh Nguyen, Christopher Leckie, James Bailey, Kotagiri Ramamohanarao

ICCV 2015 Beyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs Mehrtash Harandi, Mathieu Salzmann, Mahsa Baktashmotlagh

AAAI 2015 R1SVM: A Randomised Nonlinear Approach to Large-Scale Anomaly Detection Sarah M. Erfani, Mahsa Baktashmotlagh, Sutharshan Rajasegarar, Shanika Karunasekera, Christopher Leckie

CVPR 2014 Domain Adaptation on the Statistical Manifold Mahsa Baktashmotlagh, Mehrtash T. Harandi, Brian C. Lovell, Mathieu Salzmann

ICML 2013 Non-Linear Stationary Subspace Analysis with Application to Video Classification Mahsa Baktashmotlagh, Mehrtash Harandi, Abbas Bigdeli, Brian Lovell, Mathieu Salzmann

ICCV 2013 Unsupervised Domain Adaptation by Domain Invariant Projection Mahsa Baktashmotlagh, Mehrtash T. Harandi, Brian C. Lovell, Mathieu Salzmann