GWAS on GPUs: Streaming Data from HDD for Sustained Performance. - Lucas Beyer; Paolo Bientinesi (Euro-Par, 2013)

Streaming Data from HDD to GPUs for Sustained Peak Performance - Lucas Beyer; Paolo Bientinesi (CoRR, 2013)

Biternion Nets: Continuous Head Pose Regression from Discrete Training Labels. - Lucas Beyer; Alexander Hermans; Bastian Leibe (GCPR, 2015)

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports. - Rudolph Triebel; Kai Oliver Arras; Rachid Alami 001; Lucas Beyer; Stefan Breuers; Raja Chatila 001; Mohamed Chetouani; Daniel Cremers; Vanessa Evers; Michelangelo Fiore; Hayley Hung; Omar A. Islas Ramírez; et al. (FSR, 2015)

DROW: Real-Time Deep Learning based Wheelchair Detection in 2D Range Data. - Lucas Beyer; Alexander Hermans; Bastian Leibe (CoRR, 2016)

Towards a Principled Integration of Multi-camera Re-identification and Tracking Through Optimal Bayes Filters. - Lucas Beyer; Stefan Breuers; Vitaly Kurin; Bastian Leibe (CVPR Workshops, 2017)

In Defense of the Triplet Loss for Person Re-Identification. - Alexander Hermans; Lucas Beyer; Bastian Leibe (CoRR, 2017)

The Atari Grand Challenge Dataset. - Vitaly Kurin; Sebastian Nowozin; Katja Hofmann; Lucas Beyer; Bastian Leibe (CoRR, 2017)

DROW: Real-Time Deep Learning-Based Wheelchair Detection in 2-D Range Data. - Lucas Beyer; Alexander Hermans; Bastian Leibe (IEEE Robotics Autom. Lett., 2017)

The STRANDS Project: Long-Term Autonomy in Everyday Environments. - Nick Hawes; Christopher Burbridge; Ferdian Jovan; Lars Kunze; Bruno Lacerda; Lenka Mudrová; Jay Young; Jeremy L. Wyatt; Denise Hebesberger; Tobias Körtner; Rares Ambrus; Nils Bore; et al. (IEEE Robotics Autom. Mag., 2017)

Detection- Tracking for Efficient Person Analysis: The DetTA Pipeline. - Stefan Breuers; Lucas Beyer; Umer Rafi; Bastian Leibe (IROS, 2018)

Deep Person Detection in 2D Range Data. - Lucas Beyer; Alexander Hermans; Timm Linder; Kai Oliver Arras; Bastian Leibe (CoRR, 2018)

Deep Person Detection in Two-Dimensional Range Data. - Lucas Beyer; Alexander Hermans; Timm Linder; Kai Oliver Arras; Bastian Leibe (IEEE Robotics Autom. Lett., 2018)

Revisiting Self-Supervised Visual Representation Learning. - Alexander Kolesnikov 003; Xiaohua Zhai; Lucas Beyer (CVPR, 2019)

S4L: Self-Supervised Semi-Supervised Learning. - Lucas Beyer; Xiaohua Zhai; Avital Oliver; Alexander Kolesnikov 003 (ICCV, 2019)

S4L: Self-Supervised Semi-Supervised Learning. - Xiaohua Zhai; Avital Oliver; Alexander Kolesnikov 003; Lucas Beyer (CoRR, 2019)

Deep multi-class learning from label proportions. - Gabriel Dulac-Arnold; Neil Zeghidour; Marco Cuturi; Lucas Beyer; Jean-Philippe Vert (CoRR, 2019)

MULEX: Disentangling Exploitation from Exploration in Deep RL. - Lucas Beyer; Damien Vincent; Olivier Teboul; Sylvain Gelly; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

The Visual Task Adaptation Benchmark. - Xiaohua Zhai; Joan Puigcerver; Alexander Kolesnikov 003; Pierre Ruyssen; Carlos Riquelme; Mario Lucic; Josip Djolonga; André Susano Pinto; Maxim Neumann; Alexey Dosovitskiy; Lucas Beyer; Olivier Bachem; et al. (CoRR, 2019)

Large Scale Learning of General Visual Representations for Transfer. - Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Joan Puigcerver; Jessica Yung; Sylvain Gelly; Neil Houlsby (CoRR, 2019)

Big Transfer (BiT): General Visual Representation Learning. - Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Joan Puigcerver; Jessica Yung; Sylvain Gelly; Neil Houlsby (ECCV (5), 2020)

Are we done with ImageNet? - Lucas Beyer; Olivier J. Hénaff; Alexander Kolesnikov 003; Xiaohua Zhai; Aäron van den Oord (CoRR, 2020)

On Robustness and Transferability of Convolutional Neural Networks. - Josip Djolonga; Jessica Yung; Michael Tschannen; Rob Romijnders; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; Matthias Minderer; Alexander D'Amour; Dan Moldovan; Sylvain Gelly; Neil Houlsby; et al. (CVPR, 2021)

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. - Alexey Dosovitskiy; Lucas Beyer; Alexander Kolesnikov 003; Dirk Weissenborn; Xiaohua Zhai; Thomas Unterthiner; Mostafa Dehghani 001; Matthias Minderer; Georg Heigold; Sylvain Gelly; Jakob Uszkoreit; Neil Houlsby (ICLR, 2021)

MLP-Mixer: An all-MLP Architecture for Vision. - Ilya O. Tolstikhin; Neil Houlsby; Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Thomas Unterthiner; Jessica Yung; Andreas Steiner 001; Daniel Keysers; Jakob Uszkoreit; Mario Lucic; Alexey Dosovitskiy (NeurIPS, 2021)

SI-Score: An image dataset for fine-grained analysis of robustness to object location, rotation and size. - Jessica Yung; Rob Romijnders; Alexander Kolesnikov 003; Lucas Beyer; Josip Djolonga; Neil Houlsby; Sylvain Gelly; Mario Lucic; Xiaohua Zhai (CoRR, 2021)

A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation. - Wuyang Chen 001; Xianzhi Du; Fan Yang; Lucas Beyer; Xiaohua Zhai; Tsung-Yi Lin; Huizhong Chen; Jing Li; Xiaodan Song; Zhangyang Wang; Denny Zhou (CoRR, 2021)

Knowledge distillation: A good teacher is patient and consistent. - Lucas Beyer; Xiaohua Zhai; Amélie Royer; Larisa Markeeva; Rohan Anil; Alexander Kolesnikov 003 (CVPR, 2022)

Kubric: A scalable dataset generator. - Klaus Greff; Francois Belletti; Lucas Beyer; Carl Doersch; Yilun Du; Daniel Duckworth; David J. Fleet; Dan Gnanapragasam; Florian Golemo; Charles Herrmann; Thomas Kipf; Abhijit Kundu; et al. (CVPR, 2022)

Scaling Vision Transformers. - Xiaohua Zhai; Alexander Kolesnikov 003; Neil Houlsby; Lucas Beyer (CVPR, 2022)

LiT: Zero-Shot Transfer with Locked-image text Tuning. - Xiaohua Zhai; Xiao Wang 038; Basil Mustafa; Andreas Steiner 001; Daniel Keysers; Alexander Kolesnikov 003; Lucas Beyer (CVPR, 2022)

A Simple Single-Scale Vision Transformer for Object Detection and Instance Segmentation. - Wuyang Chen 001; Xianzhi Du; Fan Yang; Lucas Beyer; Xiaohua Zhai; Tsung-Yi Lin; Huizhong Chen; Jing Li; Xiaodan Song; Zhangyang Wang; Denny Zhou (ECCV (10), 2022)

The Efficiency Misnomer. - Mostafa Dehghani 001; Yi Tay; Anurag Arnab; Lucas Beyer; Ashish Vaswani (ICLR, 2022)

UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes. - Alexander Kolesnikov 003; André Susano Pinto; Lucas Beyer; Xiaohua Zhai; Jeremiah Harmsen; Neil Houlsby (NeurIPS, 2022)

Better plain ViT baselines for ImageNet-1k. - Lucas Beyer; Xiaohua Zhai; Alexander Kolesnikov 003 (CoRR, 2022)

PaLI: A Jointly-Scaled Multilingual Language-Image Model. - Xi Chen 071; Xiao Wang 038; Soravit Changpinyo; A. J. Piergiovanni; Piotr Padlewski; Daniel Salz; Sebastian Goodman; Adam Grycner; Basil Mustafa; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; et al. (CoRR, 2022)

VeLO: Training Versatile Learned Optimizers by Scaling Up. - Luke Metz; James Harrison; C. Daniel Freeman; Amil Merchant; Lucas Beyer; James Bradbury; Naman Agrawal; Ben Poole; Igor Mordatch; Adam Roberts; Jascha Sohl-Dickstein (CoRR, 2022)

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers. - Andreas Steiner 001; Alexander Kolesnikov 003; Xiaohua Zhai; Ross Wightman; Jakob Uszkoreit; Lucas Beyer (Trans. Mach. Learn. Res., 2022)

Deep visual human sensing with application in robotics. - Lucas Beyer (2022)

FlexiViT: One Model for All Patch Sizes. - Lucas Beyer; Pavel Izmailov; Alexander Kolesnikov 003; Mathilde Caron; Simon Kornblith; Xiaohua Zhai; Matthias Minderer; Michael Tschannen; Ibrahim Alabdulmohsin; Filip Pavetic (CVPR, 2023)

Sigmoid Loss for Language Image Pre-Training. - Xiaohua Zhai; Basil Mustafa; Alexander Kolesnikov 003; Lucas Beyer (ICCV, 2023)

PaLI: A Jointly-Scaled Multilingual Language-Image Model. - Xi Chen 071; Xiao Wang 038; Soravit Changpinyo; A. J. Piergiovanni; Piotr Padlewski; Daniel Salz; Sebastian Goodman; Adam Grycner; Basil Mustafa; Lucas Beyer; Alexander Kolesnikov 003; Joan Puigcerver; et al. (ICLR, 2023)

Scaling Vision Transformers to 22 Billion Parameters. - Mostafa Dehghani 001; Josip Djolonga; Basil Mustafa; Piotr Padlewski; Jonathan Heek; Justin Gilmer; Andreas Peter Steiner; Mathilde Caron; Robert Geirhos; Ibrahim Alabdulmohsin; Rodolphe Jenatton; Lucas Beyer; et al. (ICML, 2023)

Tuning Computer Vision Models With Task Rewards. - André Susano Pinto; Alexander Kolesnikov 003; Yuge Shi; Lucas Beyer; Xiaohua Zhai (ICML, 2023)

Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design. - Ibrahim M. Alabdulmohsin; Xiaohua Zhai; Alexander Kolesnikov 003; Lucas Beyer (NeurIPS, 2023)

Three Towers: Flexible Contrastive Learning with Pretrained Image Models. - Jannik Kossen; Mark Collier; Basil Mustafa; Xiao Wang 038; Xiaohua Zhai; Lucas Beyer; Andreas Steiner 001; Jesse Berent; Rodolphe Jenatton; Effrosyni Kokiopoulou (NeurIPS, 2023)

Image Captioners Are Scalable Vision Learners Too. - Michael Tschannen; Manoj Kumar; Andreas Steiner 001; Xiaohua Zhai; Neil Houlsby; Lucas Beyer (NeurIPS, 2023)

A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision. - Lucas Beyer; Bo Wan; Gagan Madan; Filip Pavetic; Andreas Steiner 001; Alexander Kolesnikov 003; André Susano Pinto; Emanuele Bugliarello; Xiao Wang 038; Qihang Yu; Liang-Chieh Chen; Xiaohua Zhai (CoRR, 2023)

PaLI-X: On Scaling up a Multilingual Vision and Language Model. - Xi Chen 071; Josip Djolonga; Piotr Padlewski; Basil Mustafa; Soravit Changpinyo; Jialin Wu; Carlos Riquelme Ruiz; Sebastian Goodman; Xiao Wang 038; Yi Tay; Siamak Shakeri; Mostafa Dehghani 001; et al. (CoRR, 2023)

PaLI-3 Vision Language Models: Smaller, Faster, Stronger. - Xi Chen 071; Xiao Wang 038; Lucas Beyer; Alexander Kolesnikov 003; Jialin Wu; Paul Voigtlaender; Basil Mustafa; Sebastian Goodman; Ibrahim Alabdulmohsin; Piotr Padlewski; Daniel Salz; Xi Xiong; et al. (CoRR, 2023)

On Scaling Up a Multilingual Vision and Language Model. - Xi Chen 071; Josip Djolonga; Piotr Padlewski; Basil Mustafa; Soravit Changpinyo; Jialin Wu; Carlos Riquelme Ruiz; Sebastian Goodman; Xiao Wang 038; Yi Tay; Siamak Shakeri; Mostafa Dehghani 001; et al. (CVPR, 2024)

No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models. - Angéline Pouget; Lucas Beyer; Emanuele Bugliarello; Xiao Wang 038; Andreas Steiner 001; Xiaohua Zhai; Ibrahim M. Alabdulmohsin (NeurIPS, 2024)

LocCa: Visual Pretraining with Location-aware Captioners. - Bo Wan; Michael Tschannen; Yongqin Xian; Filip Pavetic; Ibrahim M. Alabdulmohsin; Xiao Wang 038; André Susano Pinto; Andreas Steiner 001; Lucas Beyer; Xiaohua Zhai (NeurIPS, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

PaliGemma 2: A Family of Versatile VLMs for Transfer. - Andreas Steiner 001; André Susano Pinto; Michael Tschannen; Daniel Keysers; Xiao Wang 038; Yonatan Bitton; Alexey A. Gritsenko; Matthias Minderer; Anthony Sherbondy; Shangbang Long; Siyang Qin; R. Reeve Ingle; et al. (CoRR, 2024)

SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features. - Michael Tschannen; Alexey A. Gritsenko; Xiao Wang 038; Muhammad Ferjad Naeem; Ibrahim Alabdulmohsin; Nikhil Parthasarathy; Talfan Evans; Lucas Beyer; Ye Xia; Basil Mustafa; Olivier J. Hénaff; Jeremiah Harmsen; et al. (CoRR, 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)