Do Better ImageNet Models Transfer Better?

23 May 2018

Papers citing "Do Better ImageNet Models Transfer Better?"

50 / 639 papers shown

Title
Initialization Matters for Adversarial Transfer Learning Andong Hua Jindong Gu Zhiyu Xue Nicholas Carlini Eric Wong Yao Qin AAML 22 6 0 10 Dec 2023
Artificial Neural Nets and the Representation of Human Concepts Timo Freiesleben NAI 14 1 0 08 Dec 2023
A Scalable and Generalizable Pathloss Map Prediction Ju-Hyung Lee A. Molisch 18 12 0 06 Dec 2023
SASSL: Enhancing Self-Supervised Learning via Neural Style Transfer Renan A. Rojas-Gomez Karan Singhal Ali Etemad Alex Bijamov Warren Morningstar Philip Mansfield 14 1 0 02 Dec 2023
Efficient Stitchable Task Adaptation Haoyu He Zizheng Pan Jing Liu Jianfei Cai Bohan Zhuang 24 3 0 29 Nov 2023
Towards Few-shot Out-of-Distribution Detection Jiuqing Dong Yongbin Gao Heng Zhou Jun Cen Yifan Yao Sook Yoon Park Dong Sun OODD 22 3 0 20 Nov 2023
Towards interpretable-by-design deep learning algorithms Plamen Angelov D. Kangin Ziyang Zhang 16 6 0 19 Nov 2023
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy Kirill Vishniakov Zhiqiang Shen Zhuang Liu CLIP 25 16 0 15 Nov 2023
Concept-wise Fine-tuning Matters in Preventing Negative Transfer Yunqiao Yang Long-Kai Huang Ying Wei 6 2 0 12 Nov 2023
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification Reza Esfandiarpoor Stephen H. Bach VLM 19 13 0 10 Nov 2023
Exploring Dataset-Scale Indicators of Data Quality Ben Feuer Chinmay Hegde 19 1 0 07 Nov 2023
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks Micah Goldblum Hossein Souri Renkun Ni Manli Shu Viraj Prabhu ... Adrien Bardes Judy Hoffman Ramalingam Chellappa Andrew Gordon Wilson Tom Goldstein VLM 73 62 0 30 Oct 2023
MELEP: A Novel Predictive Measure of Transferability in Multi-Label ECG Diagnosis Cuong V. Nguyen H. Duong Cuong D.Do 20 4 0 27 Oct 2023
The Expressive Power of Low-Rank Adaptation Yuchen Zeng Kangwook Lee 28 49 0 26 Oct 2023
Gramian Attention Heads are Strong yet Efficient Vision Learners Jongbin Ryu Dongyoon Han J. Lim 18 1 0 25 Oct 2023
The Importance of Anti-Aliasing in Tiny Object Detection Jinlai Ning Michael W. Spratling 27 2 0 22 Oct 2023
Learning with Unmasked Tokens Drives Stronger Vision Learners Taekyung Kim Sanghyuk Chun Byeongho Heo Dongyoon Han SSL 34 1 0 20 Oct 2023
Interpreting and Controlling Vision Foundation Models via Text Explanations Haozhe Chen Junfeng Yang Carl Vondrick Chengzhi Mao 11 2 0 16 Oct 2023
A Recent Survey of Heterogeneous Transfer Learning Runxue Bao Yiming Sun Yuhe Gao Jindong Wang Qiang Yang Zhi-Hong Mao Ye Ye 22 4 0 12 Oct 2023
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis Raman Dutt Ondrej Bohdal Sotirios A. Tsaftaris Timothy M. Hospedales 16 14 0 08 Oct 2023
SPADE: Sparsity-Guided Debugging for Deep Neural Networks Arshia Soltani Moakhar Eugenia Iofinova Elias Frantar Dan Alistarh 32 1 0 06 Oct 2023
Coloring Deep CNN Layers with Activation Hue Loss Louis-Franccois Bouchard Mohsen Ben Lazreg Matthew Toews LLMSV 14 0 0 05 Oct 2023
Pre-training with Synthetic Data Helps Offline Reinforcement Learning Zecheng Wang Che Wang Zixuan Dong Keith Ross OffRL 22 5 0 01 Oct 2023
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks Hao Chen Jindong Wang Ankit Shah Ran Tao Hongxin Wei Berfin cSimcsek Masashi Sugiyama Bhiksha Raj 24 26 0 29 Sep 2023
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models Sanghwan Kim Hao Tang Fisher Yu VLM CLIP 13 4 0 28 Sep 2023
Transferability of Representations Learned using Supervised Contrastive Learning Trained on a Multi-Domain Dataset Alvin De Jun Tan Clement Tan C. Yeo 23 0 0 27 Sep 2023
Pixel-Grounded Prototypical Part Networks Zachariah Carmichael Suhas Lohit A. Cherian Michael J. Jones Walter J. Scheirer 33 11 0 25 Sep 2023
Dynamic Visual Prompt Tuning for Parameter Efficient Transfer Learning Chunqing Ruan Hongjian Wang VLM VPVLM 27 1 0 12 Sep 2023
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach KB Vimal Saketh Bachu Tanmay Garg Niveditha Lakshmi Narasimhan Raghavan Konuru Vineeth N. Balasubramanian 17 2 0 05 Sep 2023
No Data Augmentation? Alternative Regularizations for Effective Training on Small Datasets Lorenzo Brigato S. Mougiakakou 19 3 0 04 Sep 2023
DR-Tune: Improving Fine-tuning of Pretrained Visual Models by Distribution Regularization with Semantic Calibration Nana Zhou Jiaxin Chen Di Huang 17 4 0 23 Aug 2023
An Analysis of Initial Training Strategies for Exemplar-Free Class-Incremental Learning Grégoire Petit Michael Soumm Eva Feillet Adrian Daniel Popescu Bertrand Delezoide David Picard C´eline Hudelot CLL 19 7 0 22 Aug 2023
Distributionally Robust Classification on a Data Budget Ben Feuer Ameya Joshi Minh Pham C. Hegde OOD 27 2 0 07 Aug 2023
Incorporating Pre-training Data Matters in Unsupervised Domain Adaptation Yinsong Xu Aidong Men Yang Liu Qingchao Chen 16 0 0 06 Aug 2023
Accurate Neural Network Pruning Requires Rethinking Sparse Optimization Denis Kuznedelev Eldar Kurtic Eugenia Iofinova Elias Frantar Alexandra Peste Dan Alistarh VLM 14 11 0 03 Aug 2023
ETran: Energy-Based Transferability Estimation Mohsen Gholami Mohammad Akbari Xinglu Wang Behnam Kamranian Yong Zhang 13 9 0 03 Aug 2023
Gloss-free Sign Language Translation: Improving from Visual-Language Pretraining Benjia Zhou Zhigang Chen Albert Clapés Jun Wan Yanyan Liang Sergio Escalera Zhen Lei Du Zhang SLR 26 47 0 27 Jul 2023
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness Vivek Ramanujan Thao Nguyen Sewoong Oh Ludwig Schmidt Ali Farhadi OOD 14 21 0 24 Jul 2023
Optimizing PatchCore for Few/many-shot Anomaly Detection Joao Santos Triet Tran Oliver Rippel 21 10 0 20 Jul 2023
SqueezerFaceNet: Reducing a Small Face Recognition CNN Even More Via Filter Pruning F. Alonso-Fernandez Kevin Hernandez Diaz J. M. Rubio J. Bigün PICV CVBM 17 2 0 20 Jul 2023
A Holistic Assessment of the Reliability of Machine Learning Systems Anthony Corso David Karamadian Romeo Valentin Mary Cooper Mykel J. Kochenderfer 28 6 0 20 Jul 2023
Towards the Sparseness of Projection Head in Self-Supervised Learning Zeen Song Xingzhe Su Jingyao Wang Wenwen Qiang Changwen Zheng Fuchun Sun 26 3 0 18 Jul 2023
Large Class Separation is not what you need for Relational Reasoning-based OOD Detection L. Lu Giulia DÁscenzi Francesco Cappio Borlino Tatiana Tommasi OODD 22 1 0 12 Jul 2023
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation Gabriele Merlin Vedant Nanda Ruchit Rawal Mariya Toneva 15 3 0 12 Jul 2023
RanPAC: Random Projections and Pre-trained Models for Continual Learning Mark D Mcdonnell Dong Gong Amin Parvaneh Ehsan Abbasnejad A. Hengel VLM CLL 27 95 0 05 Jul 2023
Efficient Online Processing with Deep Neural Networks Lukas Hedegaard 18 0 0 23 Jun 2023
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts Annie S. Chen Yoonho Lee Amrith Rajagopal Setlur Sergey Levine Chelsea Finn OOD 14 5 0 19 Jun 2023
Partial Hypernetworks for Continual Learning Hamed Hemati Vincenzo Lomonaco D. Bacciu Damian Borth CLL 11 7 0 19 Jun 2023
Waffling around for Performance: Visual Classification with Random Words and Broad Concepts Karsten Roth Jae Myung Kim A. Sophia Koepke Oriol Vinyals Cordelia Schmid Zeynep Akata VLM 19 70 0 12 Jun 2023
Improving neural network representations using human similarity judgments Lukas Muttenthaler Lorenz Linhardt Jonas Dippel Robert A. Vandermeulen Katherine L. Hermann Andrew Kyle Lampinen Simon Kornblith 40 29 0 07 Jun 2023