Caner Hazirbas

According to our database, Caner Hazirbas authored at least 27 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

The Bias of Harmful Label Associations in Vision-Language Models.

Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark Ibrahim

CoRR, 2024

2023

Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis.

Maxim Maximov, Tim Meinhardt, Ismail Elezi, Zoe Papakipos, Caner Hazirbas, Cristian Canton-Ferrer, Laura Leal-Taixé

CoRR, 2023

Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies.

Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim

CoRR, 2023

The Casual Conversations v2 Dataset.

Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton-Ferrer, Caner Hazirbas

CoRR, 2023

Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations.

Laura Gustafson, Megan Richards, Melissa Hall, Caner Hazirbas, Diane Bouchacourt, Mark Ibrahim

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

VPA: Fully Test-Time Visual Prompt Adaptation.

Jiachen Sun, Mark Ibrahim, Melissa Hall, Ivan Evtimov, Z. Morley Mao, Cristian Canton-Ferrer, Caner Hazirbas

Proceedings of the 31st ACM International Conference on Multimedia, 2023

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Casual Conversations v2 Dataset : A diverse, large benchmark for measuring fairness and robustness in audio/vision/speech models.

Bilal Porgali, Vítor Albiero, Jordan Ryda, Cristian Canton-Ferrer, Caner Hazirbas

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others.

Zhiheng Li, Ivan Evtimov, Albert Gordo, Caner Hazirbas, Tal Hassner, Cristian Canton-Ferrer, Chenliang Xu, Mark Ibrahim

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Towards Measuring Fairness in AI: The Casual Conversations Dataset.

Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton-Ferrer

IEEE Trans. Biom. Behav. Identity Sci., 2022

Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness.

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

CoRR, 2022

Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions.

Chunxi Liu, Michael Picheny, Leda Sari, Pooja Chitkara, Alex Xiao, Xiaohui Zhang, Mark Chou, Andres Alvarado, Caner Hazirbas, Yatharth Saraf

Proceedings of the IEEE International Conference on Acoustics, 2022

Fairness Indicators for Systematic Assessments of Visual Feature Extractors.

Priya Goyal, Adriana Romero-Soriano, Caner Hazirbas, Levent Sagun, Nicolas Usunier

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Generating High Fidelity Data from Low-density Regions using Diffusion Models.

Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, Cristian Canton-Ferrer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Localized Uncertainty Attacks.

Ousmane Amadou Dia, Theofanis Karaletsos, Caner Hazirbas, Cristian Canton-Ferrer, Ilknur Kaynar Kabul, Erik Meijer

CoRR, 2021

Casual Conversations: A Dataset for Measuring Fairness in AI.

Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, Cristian Canton-Ferrer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2019

Learning Geometry and Semantics for Deep Image Restoration.

Caner Hazirbas

PhD thesis, 2019

2018

What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?

Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox

Int. J. Comput. Vis., 2018

Deep Depth from Focus.

Caner Hazirbas, Sebastian Georg Soyer, Maximilian Christian Staab, Laura Leal-Taixé, Daniel Cremers

Proceedings of the Computer Vision - ACCV 2018, 2018

2017

Deep Depth From Focus.

Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers

CoRR, 2017

Image-Based Localization Using LSTMs for Structured Feature Correlation.

Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers

Proceedings of the IEEE International Conference on Computer Vision, 2017

Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems.

Tim Meinhardt, Michael Möller, Caner Hazirbas, Daniel Cremers

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Image-based Localization with Spatial LSTMs.

Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers

CoRR, 2016

FuseNet: Incorporating Depth into Semantic Segmentation via Fusion-Based CNN Architecture.

Caner Hazirbas, Lingni Ma, Csaba Domokos, Daniel Cremers

Proceedings of the Computer Vision - ACCV 2016, 2016

2015

Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation.

Caner Hazirbas, Julia Diebold, Daniel Cremers

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

Interactive Multi-label Segmentation of RGB-D Images.

Julia Diebold, Nikolaus Demmel, Caner Hazirbas, Michael Möller, Daniel Cremers

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

FlowNet: Learning Optical Flow with Convolutional Networks.

Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015