Do Better ImageNet Models Transfer Better?

23 May 2018

Papers citing "Do Better ImageNet Models Transfer Better?"

50 / 639 papers shown

Title
No One Representation to Rule Them All: Overlapping Features of Training Methods Raphael Gontijo-Lopes Yann N. Dauphin E. D. Cubuk 18 58 0 20 Oct 2021
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs Kaichao You Yong Liu Ziyang Zhang Jianmin Wang Michael I. Jordan Mingsheng Long 103 30 0 20 Oct 2021
Learning Rich Nearest Neighbor Representations from Self-supervised Ensembles Bram Wallace Devansh Arpit Huan Wang Caiming Xiong SSL OOD 16 0 0 19 Oct 2021
Network Augmentation for Tiny Deep Learning Han Cai Chuang Gan Ji Lin Song Han 15 29 0 17 Oct 2021
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance Shibal Ibrahim Natalia Ponomareva Rahul Mazumder AAML 106 16 0 13 Oct 2021
Instance-based Label Smoothing For Better Calibrated Classification Networks Mohamed Maher Meelis Kull UQCV 6 7 0 11 Oct 2021
Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm Yangguang Li Feng Liang Lichen Zhao Yufeng Cui Wanli Ouyang Jing Shao F. Yu Junjie Yan VLM CLIP 24 442 0 11 Oct 2021
Improving Fractal Pre-training Connor Anderson Ryan Farrell 80 27 0 06 Oct 2021
Exploring the Limits of Large Scale Pre-training Samira Abnar Mostafa Dehghani Behnam Neyshabur Hanie Sedghi AI4CE 50 114 0 05 Oct 2021
Compressive Visual Representations Kuang-Huei Lee Anurag Arnab S. Guadarrama John F. Canny Ian S. Fischer SSL 57 48 0 27 Sep 2021
DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers Changlin Li Guangrun Wang Bing Wang Xiaodan Liang Zhihui Li Xiaojun Chang 25 9 0 21 Sep 2021
On the Importance of Distractors for Few-Shot Classification Rajshekhar Das Yu-xiong Wang José M. F. Moura 13 28 0 20 Sep 2021
Socially Supervised Representation Learning: the Role of Subjectivity in Learning Efficient Representations Julius Taylor Eleni Nisioti Clément Moulin-Frier 9 0 0 20 Sep 2021
A Study of the Generalizability of Self-Supervised Representations Atharva Tendle Mohammad Rashedul Hasan 62 26 0 19 Sep 2021
Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyond M. Ponti Fernando Pereira dos Santos Leo Sampaio Ferraz Ribeiro G. B. Cavallari 17 15 0 06 Sep 2021
Robust fine-tuning of zero-shot models Mitchell Wortsman Gabriel Ilharco Jong Wook Kim Mike Li Simon Kornblith ... Raphael Gontijo-Lopes Hannaneh Hajishirzi Ali Farhadi Hongseok Namkoong Ludwig Schmidt VLM 23 688 0 04 Sep 2021
Adversarial Robustness for Unsupervised Domain Adaptation Muhammad Awais Fengwei Zhou Hang Xu Lanqing Hong Ping Luo Sung-Ho Bae Zhenguo Li 18 39 0 02 Sep 2021
Efficient Visual Recognition with Deep Neural Networks: A Survey on Recent Advances and New Directions Yang Wu Dingheng Wang Xiaotong Lu Fan Yang Guoqi Li W. Dong Jianbo Shi 27 18 0 30 Aug 2021
Auxiliary Task Update Decomposition: The Good, The Bad and The Neutral Lucio Dery Yann N. Dauphin David Grangier MoMe 6 29 0 25 Aug 2021
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification Myriam Bontonou Nicolas Farrugia Vincent Gripon CML 9 0 0 23 Aug 2021
Ranking Models in Unlabeled New Environments Xiaoxiao Sun Yunzhong Hou Weijian Deng Hongdong Li Liang Zheng OOD 13 9 0 23 Aug 2021
An Attention Module for Convolutional Neural Networks Zhu Baozhou P. Hofstee Jinho Lee Zaid Al-Ars 6 23 0 18 Aug 2021
Towards Efficient and Data Agnostic Image Classification Training Pipeline for Embedded Systems K. Prokofiev V. Sovrasov 3DH 19 2 0 16 Aug 2021
Challenges for cognitive decoding using deep learning methods A. Thomas Christopher Ré R. Poldrack AI4CE 6 6 0 16 Aug 2021
ConvNets vs. Transformers: Whose Visual Representations are More Transferable? Hong-Yu Zhou Chi-Ken Lu Sibei Yang Yizhou Yu ViT 16 53 0 11 Aug 2021
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations Oliver Rippel Arnav Chavan Chucai Lei Dorit Merhof 36 18 0 09 Aug 2021
NASOA: Towards Faster Task-oriented Online Fine-tuning with a Zoo of Models Hang Xu Ning Kang Gengwei Zhang Chuanlong Xie Xiaodan Liang Zhenguo Li OnRL 21 7 0 07 Aug 2021
Generic Neural Architecture Search via Regression Yuhong Li Cong Hao Pan Li Jinjun Xiong Deming Chen 26 27 0 04 Aug 2021
Domain Adaptor Networks for Hyperspectral Image Recognition Gustavo Pérez Subhransu Maji 8 0 0 03 Aug 2021
Bias Loss for Mobile Neural Networks L. Abrahamyan Valentin Ziatchin Yiming Chen Nikos Deligiannis 9 14 0 23 Jul 2021
Non-binary deep transfer learning for image classification J. Plested Xuyang Shen Tom Gedeon MQ 28 5 0 19 Jul 2021
Level generation and style enhancement -- deep learning for game development overview P. Migdal Bartlomiej Olechno Bla.zej Podgórski GAN VLM 11 4 0 15 Jul 2021
Cats, not CAT scans: a study of dataset similarity in transfer learning for 2D medical image classification Irma van den Brandt F. Fok B. Mulders Joaquin Vanschoren V. Cheplygina 18 4 0 13 Jul 2021
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization John Miller Rohan Taori Aditi Raghunathan Shiori Sagawa Pang Wei Koh Vaishaal Shankar Percy Liang Y. Carmon Ludwig Schmidt OODD OOD 14 266 0 09 Jul 2021
Challenges for machine learning in clinical translation of big data imaging studies Nicola K. Dinsdale Emma Bluemke V. Sundaresan M. Jenkinson Stephen Smith Ana I. L. Namburete AI4CE 32 41 0 07 Jul 2021
Predicting with Confidence on Unseen Distributions Devin Guillory Vaishaal Shankar Sayna Ebrahimi Trevor Darrell Ludwig Schmidt UQCV OOD 15 115 0 07 Jul 2021
Zoo-Tuning: Adaptive Transfer from a Zoo of Models Yang Shu Zhi Kou Zhangjie Cao Jianmin Wang Mingsheng Long 10 44 0 29 Jun 2021
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers Andreas Steiner Alexander Kolesnikov Xiaohua Zhai Ross Wightman Jakob Uszkoreit Lucas Beyer ViT 34 613 0 18 Jun 2021
Joining datasets via data augmentation in the label space for neural networks Jake Zhao Mingfeng Ou Linji Xue Yunkai Cui Sai Wu Gang Chen 11 2 0 17 Jun 2021
CARTL: Cooperative Adversarially-Robust Transfer Learning Dian Chen Hongxin Hu Qian Wang Yinli Li Cong Wang Chao Shen Qi Li 15 13 0 12 Jun 2021
Probing transfer learning with a model of synthetic correlated datasets Federica Gerace Luca Saglietti Stefano Sarao Mannelli Andrew M. Saxe Lenka Zdeborová OOD 11 30 0 09 Jun 2021
Generative Models as a Data Source for Multiview Representation Learning Ali Jahanian Xavier Puig Yonglong Tian Phillip Isola 20 124 0 09 Jun 2021
GAN Cocktail: mixing GANs without dataset access Omri Avrahami Dani Lischinski Ohad Fried DiffM MoMe 18 10 0 07 Jun 2021
Personalizing Pre-trained Models Mina Khan P. Srivatsa Advait Rane Shriram Chenniappa A. Hazariwala Pattie Maes VLM 37 5 0 02 Jun 2021
One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations Henry Kvinge Scott Howland Nico Courts Lauren A. Phillips John Buckheit ... J. H. Lee Sandeep Tiwari J. Hibler Court D. Corley Nathan Oken Hodas OODD OOD 21 2 0 02 Jun 2021
Recent advances and clinical applications of deep learning in medical image analysis Xuxin Chen Ximing Wang Kecheng Zhang K. Fung T. Thai K. Moore Robert S. Mannel Hong Liu B. Zheng Y. Qiu OOD 18 568 0 27 May 2021
Improved OOD Generalization via Adversarial Training and Pre-training Mingyang Yi Lu Hou Jiacheng Sun Lifeng Shang Xin Jiang Qun Liu Zhi-Ming Ma VLM 15 83 0 24 May 2021
Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weight Ming-hui Sun Haoxuan Dou Junjie Yan 11 2 0 19 May 2021
Divide and Contrast: Self-supervised Learning from Uncurated Data Yonglong Tian Olivier J. Hénaff Aaron van den Oord SSL 51 96 0 17 May 2021
LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping Ozan Çatal W. Jansen Tim Verbelen Bart Dhoedt Jan Steckel SSL 30 17 0 07 May 2021