Caner Hazirbas

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 37

Top Venues

Technical University of Munich, Germany (PHD)

Education History

Technical University of Munich, Germany

PHD

Publications

Maxim Maximov, Tim Meinhardt, Zoe Papakipos, Caner Hazirbas, Cristian Canton, Laura Leal-Taixé
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-Identification via Full-Body Person Synthesis. FG (2024)
Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark Ibrahim
The Bias of Harmful Label Associations in Vision-Language Models. CoRR (2024)
Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton-Ferrer, Caner Hazirbas
The Casual Conversations v2 Dataset. CoRR (2023)
Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR (2023)
Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others. CVPR (2023)
Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim
Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations. NeurIPS (2023)
Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas
VPA: Fully Test-Time Visual Prompt Adaptation. CoRR (2023)
Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas
VPA: Fully Test-Time Visual Prompt Adaptation. ACM Multimedia (2023)
Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies. CoRR (2023)
Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton-Ferrer, Caner Hazirbas
The Casual Conversations v2 Dataset : A diverse, large benchmark for measuring fairness and robustness in audio/vision/speech models. CVPR Workshops (2023)
Maxim Maximov, Tim Meinhardt, Ismail Elezi, Zoe Papakipos, Caner Hazirbas, Cristian Canton, Laura Leal-Taixé
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis. CoRR (2023)
Priya Goyal, Adriana Romero-Soriano, Caner Hazirbas, Levent Sagun, Nicolas Usunier
Fairness Indicators for Systematic Assessments of Visual Feature Extractors. FAccT (2022)
Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton-Ferrer
Towards Measuring Fairness in AI: The Casual Conversations Dataset. IEEE Trans. Biom. Behav. Identity Sci. 4 (3) (2022)
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CVPR (2022)
Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others. CoRR (2022)
Chunxi Liu, Michael Picheny, Leda Sari, Pooja Chitkara, Alex Xiao, Xiaohui Zhang, Mark Chou, Andres Alvarado, Caner Hazirbas, Yatharth Saraf
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions. ICASSP (2022)
Priya Goyal, Adriana Romero-Soriano, Caner Hazirbas, Levent Sagun, Nicolas Usunier
Fairness Indicators for Systematic Assessments of Visual Feature Extractors. CoRR (2022)
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CoRR (2022)
Caner Hazirbas, Yejin Bang, Tiezheng Yu, Parisa Assar, Bilal Porgali, Vítor Albiero, Stefan Hermanek, Jacqueline Pan, Emily McReynolds, Miranda Bogen, Pascale Fung, Cristian Canton-Ferrer
Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness. CoRR (2022)
Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR (2022)
Ousmane Amadou Dia, Theofanis Karaletsos, Caner Hazirbas, Cristian Canton-Ferrer, Ilknur Kaynar Kabul, Erik Meijer
Localized Uncertainty Attacks. CoRR (2021)
Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton-Ferrer
Towards measuring fairness in AI: the Casual Conversations dataset. CoRR (2021)
Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton-Ferrer
Casual Conversations: A Dataset for Measuring Fairness in AI. CVPR Workshops (2021)
Chunxi Liu, Michael Picheny, Leda Sari, Pooja Chitkara, Alex Xiao, Xiaohui Zhang, Mark Chou, Andres Alvarado, Caner Hazirbas, Yatharth Saraf
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions. CoRR (2021)
Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? CoRR (2018)
Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? Int. J. Comput. Vis. 126 (9) (2018)
Caner Hazirbas, Sebastian Georg Soyer, Maximilian Christian Staab, Laura Leal-Taixé, Daniel Cremers
Deep Depth from Focus. ACCV (3) (2018)
Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. ICCV (2017)
Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers
Deep Depth From Focus. CoRR (2017)
Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers
Image-Based Localization Using LSTMs for Structured Feature Correlation. ICCV (2017)
Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. CoRR (2017)
Caner Hazirbas, Lingni Ma, Csaba Domokos, Daniel Cremers
FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture. ACCV (1) (2016)
Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers
Image-based Localization with Spatial LSTMs. CoRR (2016)
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox
FlowNet: Learning Optical Flow with Convolutional Networks. ICCV (2015)
Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox
FlowNet: Learning Optical Flow with Convolutional Networks. CoRR (2015)
Caner Hazirbas, Julia Diebold, Daniel Cremers
Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation. SSVM (2015)
Julia Diebold, Nikolaus Demmel, Caner Hazirbas, Michael Möller, Daniel Cremers
Interactive Multi-label Segmentation of RGB-D Images. SSVM (2015)

Caner Hazirbas.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Caner Hazirbas