Xiaohua Zhai

98 papers A* 27B 3C 1Misc 1Journal 57Unranked 9
YearRankTypeTitle / Venue / Authors
2025 J jnl
Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems.
CoRR
Andrii Balashov, Olena Ponomarova, Xiaohua Zhai
2025 J jnl
Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems.
CoRR
Ibrahim Alabdulmohsin, Xiaohua Zhai
2025 J jnl
Scaling Pre-training to One Hundred Billion Data for Vision Language Models.
CoRR
Xiao Wang, Ibrahim Alabdulmohsin, Daniel Salz, Zhe Li, Keran Rong, Xiaohua Zhai
2025 J jnl
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.
CoRR
Michael Tschannen, Alexey A. Gritsenko, Xiao Wang, Muhammad Ferjad Naeem, Ibrahim Alabdulmohsin, Nikhil Parthasarathy, Talfan Evans, Lucas Beyer, Ye Xia, Basil Mustafa, Olivier J. Hénaff, Jeremiah Harmsen, Andreas Steiner, Xiaohua Zhai
2025 J jnl
Zero-shot Autonomous Microscopy for Scalable and Intelligent Characterization of 2D Materials.
CoRR
Jingyun Yang, Ruoyan Avery Yin, Chi Jiang, Yuepeng Hu, Xiaokai Zhu, Xingjian Hu, Sutharsika Kumar, Xiao Wang, Xiaohua Zhai, Keran Rong, Yunyue Zhu, Tianyi Zhang, Zongyou Yin, Jing Kong, Neil Zhenqiang Gong, Zhichu Ren, Haozhe Wang
2024 A* conf
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
ICLR
Ibrahim Alabdulmohsin, Xiao Wang, Andreas Peter Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai
2024 J jnl
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
CoRR
Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai
2024 J jnl
Guest Editorial: Special Issue on the Promises and Dangers of Large Vision Models.
Int. J. Comput. Vis.
Kaiyang Zhou, Ziwei Liu, Xiaohua Zhai, Chunyuan Li, Kate Saenko
2024 A* conf
LocCa: Visual Pretraining with Location-aware Captioners.
NeurIPS
Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim M. Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai
2024 J jnl
LocCa: Visual Pretraining with Location-aware Captioners.
CoRR
Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim Alabdulmohsin, Xiao Wang, André Susano Pinto, Andreas Steiner, Lucas Beyer, Xiaohua Zhai
2024 A* conf
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models.
NeurIPS
Angéline Pouget, Lucas Beyer, Emanuele Bugliarello, Xiao Wang, Andreas Steiner, Xiaohua Zhai, Ibrahim M. Alabdulmohsin
2024 J jnl
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models.
CoRR
Angéline Pouget, Lucas Beyer, Emanuele Bugliarello, Xiao Wang, Andreas Peter Steiner, Xiaohua Zhai, Ibrahim Alabdulmohsin
2024 A* conf
On Scaling Up a Multilingual Vision and Language Model.
CVPR
Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2024 J jnl
PaliGemma 2: A Family of Versatile VLMs for Transfer.
CoRR
Andreas Steiner, André Susano Pinto, Michael Tschannen, Daniel Keysers, Xiao Wang, Yonatan Bitton, Alexey A. Gritsenko, Matthias Minderer, Anthony Sherbondy, Shangbang Long, Siyang Qin, R. Reeve Ingle, Emanuele Bugliarello, Sahar Kazemzadeh, Thomas Mesnard, Ibrahim Alabdulmohsin, Lucas Beyer, Xiaohua Zhai
2024 J jnl
PaliGemma: A versatile 3B VLM for transfer.
CoRR
Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai
2024 — conf
SILC: Improving Vision Language Pretraining with Self-distillation.
ECCV (21)
Muhammad Ferjad Naeem, Yongqin Xian, Xiaohua Zhai, Lukas Hoyer, Luc Van Gool, Federico Tombari
2024 J jnl
Toward a Diffusion-Based Generalist for Dense Vision Tasks.
CoRR
Yue Fan, Yongqin Xian, Xiaohua Zhai, Alexander Kolesnikov, Muhammad Ferjad Naeem, Bernt Schiele, Federico Tombari
2023 J jnl
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision.
CoRR
Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic, Andreas Steiner, Alexander Kolesnikov, André Susano Pinto, Emanuele Bugliarello, Xiao Wang, Qihang Yu, Liang-Chieh Chen, Xiaohua Zhai
2023 A* conf
FlexiViT: One Model for All Patch Sizes.
CVPR
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2023 A* conf
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design.
NeurIPS
Ibrahim M. Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer
2023 J jnl
Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design.
CoRR
Ibrahim Alabdulmohsin, Xiaohua Zhai, Alexander Kolesnikov, Lucas Beyer
2023 A* conf
Image Captioners Are Scalable Vision Learners Too.
NeurIPS
Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer
2023 J jnl
Image Captioners Are Scalable Vision Learners Too.
CoRR
Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby, Lucas Beyer
2023 J jnl
PaLI-3 Vision Language Models: Smaller, Faster, Stronger.
CoRR
Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov, Jialin Wu, Paul Voigtlaender, Basil Mustafa, Sebastian Goodman, Ibrahim Alabdulmohsin, Piotr Padlewski, Daniel Salz, Xi Xiong, Daniel Vlasic, Filip Pavetic, Keran Rong, Tianli Yu, Daniel Keysers, Xiaohua Zhai, Radu Soricut
2023 J jnl
PaLI-X: On Scaling up a Multilingual Vision and Language Model.
CoRR
Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, A. J. Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2023 J jnl
SILC: Improving Vision Language Pretraining with Self-Distillation.
CoRR
Muhammad Ferjad Naeem, Yongqin Xian, Xiaohua Zhai, Lukas Hoyer, Luc Van Gool, Federico Tombari
2023 A* conf
Scaling Vision Transformers to 22 Billion Parameters.
ICML
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby
2023 J jnl
Scaling Vision Transformers to 22 Billion Parameters.
CoRR
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
2023 A* conf
Sigmoid Loss for Language Image Pre-Training.
ICCV
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer
2023 J jnl
Sigmoid Loss for Language Image Pre-Training.
CoRR
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, Lucas Beyer
2023 A* conf
Three Towers: Flexible Contrastive Learning with Pretrained Image Models.
NeurIPS
Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
2023 J jnl
Three Towers: Flexible Contrastive Learning with Pretrained Image Models.
CoRR
Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou
2023 A* conf
Tuning Computer Vision Models With Task Rewards.
ICML
André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai
2023 J jnl
Tuning computer vision models with task rewards.
CoRR
André Susano Pinto, Alexander Kolesnikov, Yuge Shi, Lucas Beyer, Xiaohua Zhai
2022 — conf
A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation.
ECCV (10)
Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou
2022 J jnl
Better plain ViT baselines for ImageNet-1k.
CoRR
Lucas Beyer, Xiaohua Zhai, Alexander Kolesnikov
2022 J jnl
FlexiViT: One Model for All Patch Sizes.
CoRR
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
2022 J jnl
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.
Trans. Mach. Learn. Res.
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer
2022 A* conf
Knowledge distillation: A good teacher is patient and consistent.
CVPR
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
2022 A* conf
LiT: Zero-Shot Transfer with Locked-image text Tuning.
CVPR
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
2022 J jnl
PaLI: A Jointly-Scaled Multilingual Language-Image Model.
CoRR
Xi Chen, Xiao Wang, Soravit Changpinyo, A. J. Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish V. Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
2022 A* conf
Revisiting Neural Scaling Laws in Language and Vision.
NeurIPS
Ibrahim M. Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai
2022 J jnl
Revisiting Neural Scaling Laws in Language and Vision.
CoRR
Ibrahim Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai
2022 A* conf
Scaling Vision Transformers.
CVPR
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
2022 J jnl
Simple Open-Vocabulary Object Detection with Vision Transformers.
CoRR
Matthias Minderer, Alexey A. Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby
2022 — conf
Simple Open-Vocabulary Object Detection.
ECCV (10)
Matthias Minderer, Alexey A. Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby
2022 A* conf
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes.
NeurIPS
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
2022 J jnl
UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes.
CoRR
Alexander Kolesnikov, André Susano Pinto, Lucas Beyer, Xiaohua Zhai, Jeremiah Harmsen, Neil Houlsby
2022 J jnl
Underspecification Presents Challenges for Credibility in Modern Machine Learning.
J. Mach. Learn. Res.
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
2021 J jnl
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation.
CoRR
Wuyang Chen, Xianzhi Du, Fan Yang, Lucas Beyer, Xiaohua Zhai, Tsung-Yi Lin, Huizhong Chen, Jing Li, Xiaodan Song, Zhangyang Wang, Denny Zhou
2021 — conf
A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches.
NeurIPS Datasets and Benchmarks
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
2021 A* conf
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
ICLR
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
2021 J jnl
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark.
CoRR
Vincent Dumoulin, Neil Houlsby, Utku Evci, Xiaohua Zhai, Ross Goroshin, Sylvain Gelly, Hugo Larochelle
2021 J jnl
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers.
CoRR
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer
2021 J jnl
Knowledge distillation: A good teacher is patient and consistent.
CoRR
Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
2021 J jnl
LiT: Zero-Shot Transfer with Locked-image Text Tuning.
CoRR
Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
2021 A* conf
MLP-Mixer: An all-MLP Architecture for Vision.
NeurIPS
Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
2021 J jnl
MLP-Mixer: An all-MLP Architecture for Vision.
CoRR
Ilya O. Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Andreas Steiner, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, Alexey Dosovitskiy
2021 A* conf
On Robustness and Transferability of Convolutional Neural Networks.
CVPR
Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic
2021 A* conf
Revisiting the Calibration of Modern Neural Networks.
NeurIPS
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
2021 J jnl
Revisiting the Calibration of Modern Neural Networks.
CoRR
Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
2021 J jnl
SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size.
CoRR
Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai
2021 J jnl
Scaling Vision Transformers.
CoRR
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
2020 J jnl
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
CoRR
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby
2020 J jnl
Are we done with ImageNet?
CoRR
Lucas Beyer, Olivier J. Hénaff, Alexander Kolesnikov, Xiaohua Zhai, Aäron van den Oord
2020 — conf
Big Transfer (BiT): General Visual Representation Learning.
ECCV (5)
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
2020 J jnl
On Robustness and Transferability of Convolutional Neural Networks.
CoRR
Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic
2020 C conf
Training General Representations for Remote Sensing Using in-Domain Knowledge.
IGARSS
Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby
2020 J jnl
Training general representations for remote sensing using in-domain knowledge.
CoRR
Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby
2020 J jnl
Underspecification Presents Challenges for Credibility in Modern Machine Learning.
CoRR
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
2019 A* conf
A Large-Scale Study on Regularization and Normalization in GANs.
ICML
Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
2019 A* conf
High-Fidelity Image Generation With Fewer Labels.
ICML
Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly
2019 J jnl
High-Fidelity Image Generation With Fewer Labels.
CoRR
Mario Lucic, Michael Tschannen, Marvin Ritter, Xiaohua Zhai, Olivier Bachem, Sylvain Gelly
2019 J jnl
In-domain representation learning for remote sensing.
CoRR
Maxim Neumann, André Susano Pinto, Xiaohua Zhai, Neil Houlsby
2019 J jnl
Large Scale Learning of General Visual Representations for Transfer.
CoRR
Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby
2019 A* conf
Revisiting Self-Supervised Visual Representation Learning.
CVPR
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
2019 J jnl
Revisiting Self-Supervised Visual Representation Learning.
CoRR
Alexander Kolesnikov, Xiaohua Zhai, Lucas Beyer
2019 J jnl
S
CoRR
Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, Lucas Beyer
2019 A* conf
S4L: Self-Supervised Semi-Supervised Learning.
ICCV
Lucas Beyer, Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov
2019 A* conf
Self-Supervised GANs via Auxiliary Rotation Loss.
CVPR
Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby
2019 J jnl
The Visual Task Adaptation Benchmark.
CoRR
Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby
2018 J jnl
MemGEN: Memory is All You Need.
CoRR
Sylvain Gelly, Karol Kurach, Marcin Michalski, Xiaohua Zhai
2018 J jnl
Self-Supervised GAN to Counter Forgetting.
CoRR
Ting Chen, Xiaohua Zhai, Neil Houlsby
2018 J jnl
Self-Supervised Generative Adversarial Networks.
CoRR
Ting Chen, Xiaohua Zhai, Marvin Ritter, Mario Lucic, Neil Houlsby
2018 J jnl
The GAN Landscape: Losses, Architectures, Regularization, and Normalization.
CoRR
Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
2016 J jnl
Semi-Supervised Cross-Media Feature Learning With Unified Patch Graph Regularization.
IEEE Trans. Circuits Syst. Video Technol.
Yuxin Peng, Xiaohua Zhai, Yunzhen Zhao, Xin Huang
2014 J jnl
Learning Cross-Media Joint Representation With Sparse and Semisupervised Regularization.
IEEE Trans. Circuits Syst. Video Technol.
Xiaohua Zhai, Yuxin Peng, Jianguo Xiao
2013 B conf
Cross-media retrieval by cluster-based correlation analysis.
ICIP
Ding Ma, Xiaohua Zhai, Yuxin Peng
2013 J jnl
Cross-media retrieval by intra-media and inter-media correlation mining.
Multim. Syst.
Xiaohua Zhai, Yuxin Peng, Jianguo Xiao
2013 A* conf
Heterogeneous Metric Learning with Joint Graph Regularization for Cross-Media Retrieval.
AAAI
Xiaohua Zhai, Yuxin Peng, Jianguo Xiao
2013 — conf
PKU_ICST at TRECVID2013 : Instance Search Task.
TRECVID
Yuxin Peng, Xiaohua Zhai, Jian Zhang, Lei Huang, Nianzu Li, Panpan Tang, Xin Huang, Yunzhen Zhao
2012 Misc conf
Cross-modality correlation propagation for cross-media retrieval.
ICASSP
Xiaohua Zhai, Yuxin Peng, Jianguo Xiao
2012 B conf
Effective Heterogeneous Similarity Measure with Nearest Neighbors for Cross-Media Retrieval.
MMM
Xiaohua Zhai, Yuxin Peng, Jianguo Xiao
2012 A* conf
PDSS: patch-descriptor-similarity space for effective face verification.
ACM Multimedia
Xiaohua Zhai, Yuxin Peng, Jianguo Xiao
2012 — conf
PKU-ICST @TRECVID2012: Known-item Search Task.
TRECVID
Yuxin Peng, Yunbo Peng, Xiaohua Zhai, Jian Zhang, Tianjun Xiao, Xin Huang, Kang Cai
2012 B conf
Tri-space and ranking based heterogeneous similarity measure for cross-media retrieval.
ICPR
Li Ling, Xiaohua Zhai, Yuxin Peng
2009 — conf
PKU-ICST at TRECVID2009: High Level Feature Extraction and Search.
TRECVID
Yuxin Peng, Zhiguo Yang, Lei Cao, Jian Yi, Ning Wan, Yuan Feng, Xiaohua Zhai, En Shi, Hao Li
2006 — conf
Adaptive Control Based on Recurrent Fuzzy Wavelet Neural Network and Its Application on Robotic Tracking Control.
ISNN (2)
Wei Sun, Yaonan Wang, Xiaohua Zhai