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A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification

28 November 2022

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Papers citing "A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification"

24 / 24 papers shown

Title
Interpretable Failure Detection with Human-Level Concepts Kien X. Nguyen Tang Li Xi Peng 113 1 0 07 Feb 2025
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications Jordy Van Landeghem Subhajit Maity Ayan Banerjee Matthew Blaschko Marie-Francine Moens Josep Lladós Sanket Biswas 112 2 0 12 Jun 2024
Rejection via Learning Density Ratios Alexander Soen Hisham Husain Philip Schulz Vu-Linh Nguyen 122 2 0 29 May 2024
Plex: Towards Reliability using Pretrained Large Model Extensions Dustin Tran J. Liu Michael W. Dusenberry Du Phan Mark Collier ... D. Sculley Y. Gal Zoubin Ghahramani Jasper Snoek Balaji Lakshminarayanan VLM 108 126 0 15 Jul 2022
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts Weixin Liang James Zou OOD 76 84 0 14 Feb 2022
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection Jie Jessie Ren Stanislav Fort J. Liu Abhijit Guha Roy Shreyas Padhy Balaji Lakshminarayanan UQCV 173 225 0 16 Jun 2021
Common Limitations of Image Processing Metrics: A Picture Story Annika Reinke M. Tizabi Carole H. Sudre Matthias Eisenmann Tim Radsch ... Gaël Varoquaux Manuel Wiesenfarth Ziv R. Yaniv Paul Jäger Lena Maier-Hein 69 146 0 12 Apr 2021
Post-hoc Uncertainty Calibration for Domain Drift Scenarios Christian Tomani Sebastian Gruber Muhammed Ebrar Erdem Daniel Cremers Florian Buettner UQCV 170 67 0 20 Dec 2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 183 1,434 0 14 Dec 2020
A Unifying Review of Deep and Shallow Anomaly Detection Lukas Ruff Jacob R. Kauffmann Robert A. Vandermeulen G. Montavon Wojciech Samek Marius Kloft Thomas G. Dietterich Klaus-Robert Muller UQCV 117 800 0 24 Sep 2020
BREEDS: Benchmarks for Subpopulation Shift Shibani Santurkar Dimitris Tsipras Aleksander Madry OOD 59 175 0 11 Aug 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 211 2,056 0 16 Apr 2020
Hybrid Models for Open Set Recognition Hongjie Zhang Ang Li Jie Guo Yanwen Guo BDL 135 185 0 27 Mar 2020
Detecting semantic anomalies Faruk Ahmed Aaron Courville 50 83 0 13 Aug 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 170 1,704 0 06 Jun 2019
SelectiveNet: A Deep Neural Network with an Integrated Reject Option Yonatan Geifman Ran El-Yaniv CVBM OOD 126 311 0 26 Jan 2019
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 187 2,060 0 10 Jul 2018
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 179 473 0 30 May 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 193 922 0 28 Feb 2018
Selective Classification for Deep Neural Networks Yonatan Geifman Ran El-Yaniv CVBM 95 529 0 23 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 359 4,718 0 15 Mar 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 166 3,468 0 07 Oct 2016
SGDR: Stochastic Gradient Descent with Warm Restarts I. Loshchilov Frank Hutter ODL 333 8,169 0 13 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 831 9,345 0 06 Jun 2015