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Bottleneck Transformers for Visual Recognition


Jan 27, 2021
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani

* Technical Report, 20 pages, 13 figures, 19 tables 

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Mitigating bias in calibration error estimation


Dec 15, 2020
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer


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Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation


May 22, 2020
Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, Jonathon Shlens

* 21 pages including reference 

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Streaming Object Detection for 3-D Point Clouds


May 04, 2020
Wei Han, Zhengdong Zhang, Benjamin Caine, Brandon Yang, Christoph Sprunk, Ouais Alsharif, Jiquan Ngiam, Vijay Vasudevan, Jonathon Shlens, Zhifeng Chen


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Improving 3D Object Detection through Progressive Population Based Augmentation


Apr 02, 2020
Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov


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Revisiting Spatial Invariance with Low-Rank Local Connectivity


Feb 07, 2020
Gamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith


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Scalability in Perception for Autonomous Driving: Waymo Open Dataset


Dec 18, 2019
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov


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RandAugment: Practical automated data augmentation with a reduced search space


Nov 14, 2019
Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le

* Added ablation experiments 

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RandAugment: Practical data augmentation with no separate search


Sep 30, 2019
Ekin D. Cubuk, Barret Zoph, Jonathon Shlens, Quoc V. Le


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StarNet: Targeted Computation for Object Detection in Point Clouds


Aug 29, 2019
Jiquan Ngiam, Benjamin Caine, Wei Han, Brandon Yang, Yuning Chai, Pei Sun, Yin Zhou, Xi Yi, Ouais Alsharif, Patrick Nguyen, Zhifeng Chen, Jonathon Shlens, Vijay Vasudevan


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Learning Data Augmentation Strategies for Object Detection


Jun 26, 2019
Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi, Tsung-Yi Lin, Jonathon Shlens, Quoc V. Le


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A Fourier Perspective on Model Robustness in Computer Vision


Jun 21, 2019
Dong Yin, Raphael Gontijo Lopes, Jonathon Shlens, Ekin D. Cubuk, Justin Gilmer


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Stand-Alone Self-Attention in Vision Models


Jun 13, 2019
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, Jonathon Shlens


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Visual Wake Words Dataset


Jun 12, 2019
Aakanksha Chowdhery, Pete Warden, Jonathon Shlens, Andrew Howard, Rocky Rhodes

* 10 pages, 4 figures 

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Using learned optimizers to make models robust to input noise


Jun 08, 2019
Luke Metz, Niru Maheswaranathan, Jonathon Shlens, Jascha Sohl-Dickstein, Ekin D. Cubuk


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Using Videos to Evaluate Image Model Robustness


Apr 24, 2019
Keren Gu, Brandon Yang, Jiquan Ngiam, Quoc Le, Jonathon Shlens


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Attention Augmented Convolutional Networks


Apr 22, 2019
Irwan Bello, Barret Zoph, Ashish Vaswani, Jonathon Shlens, Quoc V. Le


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A Learned Representation for Scalable Vector Graphics


Apr 04, 2019
Raphael Gontijo Lopes, David Ha, Douglas Eck, Jonathon Shlens


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Accelerating Training of Deep Neural Networks with a Standardization Loss


Mar 03, 2019
Jasmine Collins, Johannes Balle, Jonathon Shlens

* Technical report. Results presented at WiML 2018 

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Searching for Efficient Multi-Scale Architectures for Dense Image Prediction


Sep 11, 2018
Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, Jonathon Shlens

* Accepted by NIPS 2018 

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Progressive Neural Architecture Search


Jul 26, 2018
Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan Yuille, Jonathan Huang, Kevin Murphy

* To appear in ECCV 2018 as oral. The code and checkpoint for PNASNet-5 trained on ImageNet (both Mobile and Large) can now be downloaded from https://github.com/tensorflow/models/tree/master/research/slim#Pretrained. Also see https://github.com/chenxi116/PNASNet.TF for refactored and simplified TensorFlow code; see https://github.com/chenxi116/PNASNet.pytorch for exact conversion to PyTorch 

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A Dataset and Architecture for Visual Reasoning with a Working Memory


Jul 20, 2018
Guangyu Robert Yang, Igor Ganichev, Xiao-Jing Wang, Jonathon Shlens, David Sussillo


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Do Better ImageNet Models Transfer Better?


May 23, 2018
Simon Kornblith, Jonathon Shlens, Quoc V. Le


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Learning Transferable Architectures for Scalable Image Recognition


Apr 11, 2018
Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc V. Le


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Recurrent Segmentation for Variable Computational Budgets


Mar 15, 2018
Lane McIntosh, Niru Maheswaranathan, David Sussillo, Jonathon Shlens


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Exploring the structure of a real-time, arbitrary neural artistic stylization network


Aug 24, 2017
Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin, Jonathon Shlens

* Accepted as an oral presentation at British Machine Vision Conference (BMVC) 2017 

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Conditional Image Synthesis With Auxiliary Classifier GANs


Jul 20, 2017
Augustus Odena, Christopher Olah, Jonathon Shlens


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PixColor: Pixel Recursive Colorization


Jun 05, 2017
Sergio Guadarrama, Ryan Dahl, David Bieber, Mohammad Norouzi, Jonathon Shlens, Kevin Murphy


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YouTube-BoundingBoxes: A Large High-Precision Human-Annotated Data Set for Object Detection in Video


Mar 24, 2017
Esteban Real, Jonathon Shlens, Stefano Mazzocchi, Xin Pan, Vincent Vanhoucke

* Accepted at the Conference on Computer Vision and Pattern Recognition (CVPR) 2017 

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Pixel Recursive Super Resolution


Mar 22, 2017
Ryan Dahl, Mohammad Norouzi, Jonathon Shlens


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