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Caner Hazirbas
Person information
- unicode name: Caner Hazırbaş
- affiliation (PhD 2019): Technical University of Munich, Germany
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2020 – today
- 2024
- [c17]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: 1-10 - [i19]Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark Ibrahim:
The Bias of Harmful Label Associations in Vision-Language Models. CoRR abs/2402.07329 (2024) - [i18]Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim:
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling. CoRR abs/2408.04810 (2024) - 2023
- [c16]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: 10-17 - [c15]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: 20071-20082 - [c14]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 - [c13]Jiachen Sun
, Mark Ibrahim
VPA: Fully Test-Time Visual Prompt Adaptation. ACM Multimedia 2023: 5796-5806 - [c12]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 - [i17]Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton-Ferrer, Caner Hazirbas:
The Casual Conversations v2 Dataset. CoRR abs/2303.04838 (2023) - [i16]Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim:
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies. CoRR abs/2304.05391 (2023) - [i15]Maxim Maximov, Tim Meinhardt, Ismail Elezi, Zoe Papakipos, Caner Hazirbas, Cristian Canton-Ferrer, Laura Leal-Taixé:
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis. CoRR abs/2306.11710 (2023) - [i14]Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas:
VPA: Fully Test-Time Visual Prompt Adaptation. CoRR abs/2309.15251 (2023) - 2022
- [j2]Caner Hazirbas
Towards Measuring Fairness in AI: The Casual Conversations Dataset. IEEE Trans. Biom. Behav. Identity Sci. 4(3): 324-332 (2022) - [c11]Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer:
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CVPR 2022: 11482-11491 - [c10]Priya Goyal, Adriana Romero-Soriano, Caner Hazirbas, Levent Sagun, Nicolas Usunier:
Fairness Indicators for Systematic Assessments of Visual Feature Extractors. FAccT 2022: 70-88 - [c9]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: 6162-6166 - [i13]Priya Goyal, Adriana Romero-Soriano, Caner Hazirbas, Levent Sagun, Nicolas Usunier:
Fairness Indicators for Systematic Assessments of Visual Feature Extractors. CoRR abs/2202.07603 (2022) - [i12]Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer:
Generating High Fidelity Data from Low-density Regions using Diffusion Models. CoRR abs/2203.17260 (2022) - [i11]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 abs/2211.01866 (2022) - [i10]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 abs/2211.05809 (2022) - [i9]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 abs/2212.04825 (2022) - 2021
- [c8]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: 2289-2293 - [i8]Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton-Ferrer:
Towards measuring fairness in AI: the Casual Conversations dataset. CoRR abs/2104.02821 (2021) - [i7]Ousmane Amadou Dia, Theofanis Karaletsos, Caner Hazirbas, Cristian Canton-Ferrer, Ilknur Kaynar Kabul, Erik Meijer:
Localized Uncertainty Attacks. CoRR abs/2106.09222 (2021) - [i6]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 abs/2111.09983 (2021)
2010 – 2019
- 2019
- [b1]Caner Hazirbas:
Learning Geometry and Semantics for Deep Image Restoration. Technical University of Munich, Germany, 2019 - 2018
- [j1]Nikolaus Mayer
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? Int. J. Comput. Vis. 126(9): 942-960 (2018) - [c7]Caner Hazirbas, Sebastian Georg Soyer, Maximilian Christian Staab, Laura Leal-Taixé, Daniel Cremers
Deep Depth from Focus. ACCV (3) 2018: 525-541 - [i5]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 abs/1801.06397 (2018) - 2017
- [c6]Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers
Image-Based Localization Using LSTMs for Structured Feature Correlation. ICCV 2017: 627-637 - [c5]Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. ICCV 2017: 1799-1808 - [i4]Caner Hazirbas
Deep Depth From Focus. CoRR abs/1704.01085 (2017) - [i3]Tim Meinhardt, Michael Möller, Caner Hazirbas
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems. CoRR abs/1704.03488 (2017) - 2016
- [c4]Caner Hazirbas, Lingni Ma, Csaba Domokos, Daniel Cremers
FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture. ACCV (1) 2016: 213-228 - [i2]Florian Walch, Caner Hazirbas
Image-based Localization with Spatial LSTMs. CoRR abs/1611.07890 (2016) - 2015
- [c3]Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt
FlowNet: Learning Optical Flow with Convolutional Networks. ICCV 2015: 2758-2766 - [c2]Caner Hazirbas, Julia Diebold, Daniel Cremers
Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation. SSVM 2015: 243-255 - [c1]Julia Diebold, Nikolaus Demmel, Caner Hazirbas, Michael Möller, Daniel Cremers
Interactive Multi-label Segmentation of RGB-D Images. SSVM 2015: 294-306 - [i1]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 abs/1504.06852 (2015)
Coauthor Index
aka: Cristian Canton-Ferrer
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