A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes

26 January 2022

Papers citing "A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes"

8 / 8 papers shown

Title
Corner Cases: How Size and Position of Objects Challenge ImageNet-Trained Models Mishal Fatima Steffen Jung M. Keuper 33 0 0 06 May 2025
The PanAf-FGBG Dataset: Understanding the Impact of Backgrounds in Wildlife Behaviour Recognition Otto Brookes Maksim Kukushkin Majid Mirmehdi Colleen Stephens Paula Dieguez ... Lukas Boesch Thomas Schmid M. Arandjelovic H. Kühl T. Burghardt 46 0 0 28 Feb 2025
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations Raha Ahmadi Mohammad Javad Rajabi Mohammad Khalooiem Mohammad Sabokrou 19 0 0 04 Jul 2023
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning Yu Yang Besmira Nushi Hamid Palangi Baharan Mirzasoleiman 26 36 0 08 Apr 2023
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers Wanqian Yang Polina Kirichenko Micah Goldblum A. Wilson DRL 4 10 0 28 Nov 2022
On Feature Learning in the Presence of Spurious Correlations Pavel Izmailov Polina Kirichenko Nate Gruver A. Wilson 21 116 0 20 Oct 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 29 314 0 06 Apr 2022
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models Tianlu Wang Rohit Sridhar Diyi Yang Xuezhi Wang AAML 118 70 0 14 Oct 2021