Lucas Beyer

79 papers A* 22A 1Journal 49Unranked 6
YearRankTypeTitle / Venue / Authors
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
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
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 A* conf
PaLI: A Jointly-Scaled Multilingual Language-Image Model.
ICLR
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
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 — —
Deep visual human sensing with application in robotics.
Lucas Beyer
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
Kubric: A scalable dataset generator.
CVPR
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, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi
2022 J jnl
Kubric: A scalable dataset generator.
CoRR
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, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi
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
Scaling Vision Transformers.
CVPR
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
2022 A* conf
The Efficiency Misnomer.
ICLR
Mostafa Dehghani, Yi Tay, Anurag Arnab, Lucas Beyer, Ashish Vaswani
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
VeLO: Training Versatile Learned Optimizers by Scaling Up.
CoRR
Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein
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 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
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 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
2021 J jnl
The Efficiency Misnomer.
CoRR
Mostafa Dehghani, Anurag Arnab, Lucas Beyer, Ashish Vaswani, Yi Tay
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
2019 J jnl
Deep multi-class learning from label proportions.
CoRR
Gabriel Dulac-Arnold, Neil Zeghidour, Marco Cuturi, Lucas Beyer, Jean-Philippe Vert
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 J jnl
MULEX: Disentangling Exploitation from Exploration in Deep RL.
CoRR
Lucas Beyer, Damien Vincent, Olivier Teboul, Sylvain Gelly, Matthieu Geist, Olivier Pietquin
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 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
Deep Person Detection in 2D Range Data.
CoRR
Lucas Beyer, Alexander Hermans, Timm Linder, Kai Oliver Arras, Bastian Leibe
2018 J jnl
Deep Person Detection in Two-Dimensional Range Data.
IEEE Robotics Autom. Lett.
Lucas Beyer, Alexander Hermans, Timm Linder, Kai Oliver Arras, Bastian Leibe
2018 A conf
Detection- Tracking for Efficient Person Analysis: The DetTA Pipeline.
IROS
Stefan Breuers, Lucas Beyer, Umer Rafi, Bastian Leibe
2018 J jnl
Detection-Tracking for Efficient Person Analysis: The DetTA Pipeline.
CoRR
Stefan Breuers, Lucas Beyer, Umer Rafi, Bastian Leibe
2017 J jnl
DROW: Real-Time Deep Learning-Based Wheelchair Detection in 2-D Range Data.
IEEE Robotics Autom. Lett.
Lucas Beyer, Alexander Hermans, Bastian Leibe
2017 J jnl
In Defense of the Triplet Loss for Person Re-Identification.
CoRR
Alexander Hermans, Lucas Beyer, Bastian Leibe
2017 J jnl
The Atari Grand Challenge Dataset.
CoRR
Vitaly Kurin, Sebastian Nowozin, Katja Hofmann, Lucas Beyer, Bastian Leibe
2017 J jnl
The STRANDS Project: Long-Term Autonomy in Everyday Environments.
IEEE Robotics Autom. Mag.
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, John Folkesson, Patric Jensfelt, Lucas Beyer, Alexander Hermans, Bastian Leibe, Aitor Aldoma, Thomas Faulhammer, Michael Zillich, Markus Vincze, Eris Chinellato, Muhannad Al-Omari, Paul Duckworth, Yiannis Gatsoulis, David C. Hogg, Anthony G. Cohn, Christian Dondrup, Jaime Pulido Fentanes, Tomás Krajník, João Machado Santos, Tom Duckett, Marc Hanheide
2017 J jnl
Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters.
CoRR
Lucas Beyer, Stefan Breuers, Vitaly Kurin, Bastian Leibe
2017 — conf
Towards a Principled Integration of Multi-camera Re-identification and Tracking Through Optimal Bayes Filters.
CVPR Workshops
Lucas Beyer, Stefan Breuers, Vitaly Kurin, Bastian Leibe
2016 J jnl
DROW: Real-Time Deep Learning based Wheelchair Detection in 2D Range Data.
CoRR
Lucas Beyer, Alexander Hermans, Bastian Leibe
2016 J jnl
The STRANDS Project: Long-Term Autonomy in Everyday Environments.
CoRR
Nick Hawes, Chris Burbridge, Ferdian Jovan, Lars Kunze, Bruno Lacerda, Lenka Mudrová, Jay Young, Jeremy L. Wyatt, Denise Hebesberger, Tobias Körtner, Rares Ambrus, Nils Bore, John Folkesson, Patric Jensfelt, Lucas Beyer, Alexander Hermans, Bastian Leibe, Aitor Aldoma, Thomas Faulhammer, Michael Zillich, Markus Vincze, Muhannad Al-Omari, Eris Chinellato, Paul Duckworth, Yiannis Gatsoulis, David C. Hogg, Anthony G. Cohn, Christian Dondrup, Jaime Pulido Fentanes, Tomás Krajník, João Machado Santos, Tom Duckett, Marc Hanheide
2015 — conf
Biternion Nets: Continuous Head Pose Regression from Discrete Training Labels.
GCPR
Lucas Beyer, Alexander Hermans, Bastian Leibe
2015 — conf
SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports.
FSR
Rudolph Triebel, Kai Oliver Arras, Rachid Alami, Lucas Beyer, Stefan Breuers, Raja Chatila, Mohamed Chetouani, Daniel Cremers, Vanessa Evers, Michelangelo Fiore, Hayley Hung, Omar A. Islas Ramírez, Michiel Joosse, Harmish Khambhaita, Tomasz Kucner, Bastian Leibe, Achim J. Lilienthal, Timm Linder, Manja Lohse, Martin Magnusson, Billy Okal, Luigi Palmieri, Umer Rafi, Marieke van Rooij, Lu Zhang
2013 — conf
GWAS on GPUs: Streaming Data from HDD for Sustained Performance.
Euro-Par
Lucas Beyer, Paolo Bientinesi
2013 J jnl
Streaming Data from HDD to GPUs for Sustained Peak Performance
CoRR
Lucas Beyer, Paolo Bientinesi