Fetching the paper…
Reading the bibliography…
Computer Vision (CV) has achieved remarkable results, outperforming humans in several tasks.
Predictive inequity in object detection
Benjamin Wilson, Judy Hoffman, and Jamie Morgenstern · 1902
Earlier work this paper cites.
Face-ism: Five studies of sex differences in facial prominence
Dane Archer, Bonita Iritani, Debra D. Kimes, and Micheal Barrios · 1983
Earlier work this paper cites.
Framing: Toward clarification of a fractured paradigm
Robert M. Entman · 1993
Earlier work this paper cites.
Regularized multi–task learning
Theodoros Evgeniou and Massimiliano Pontil · 2004
Earlier work this paper cites.
Procedures for performing systematic reviews
Barbara Kitchenham · 2004
Earlier work this paper cites.
Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
Li Fei-Fei, Rob Fergus, and Pietro Perona · 2004
Earlier work this paper cites.
Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments
Gary B. Huang, Marwan Mattar, Tamara Berg, and Eric Learned-Miller · 2008
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Attribute and simile classifiers for face verification
Neeraj Kumar, Alexander C. Berg, Peter N. Belhumeur, and Shree K. Nayar · 2009
Earlier work this paper cites.
Framing the pictures in our heads: Exploring the framing and agenda-setting effects of visual images
Renita Coleman · 2010
Earlier work this paper cites.
Genetic Basis of Human Biodiversity: An Update , pages 97–119
Guido Barbujani and Vincenza Colonna · 2011
Earlier work this paper cites.
Obesity Stigma in Online News: a Visual Content Analysis
Chealse A. Heuer, Kimberly J. McClure, and Rebecca M. Puhl · 2011
Earlier work this paper cites.
Learning to share visual appearance for multiclass object detection
Ruslan Salakhutdinov, Antonio Torralba, and Joshua B. Tenenbaum · 2011
Earlier work this paper cites.
Unbiased look at dataset bias
Antonio Torralba and Alexei A. Efros · 2011
Earlier work this paper cites.
Specchio delle sue brame: analisi socio-politica delle pubblicità : genere, classe, razza, età ed eterosessismo
Laura Corradi · 2012
Earlier work this paper cites.
Undoing the damage of dataset bias
Aditya Khosla, Tinghui Zhou, Tomasz Malisiewicz, Alexei A. Efros, and Antonio Torralba · 2012
Earlier work this paper cites.
Face recognition performance: Role of demographic information
Brendan Klare, Mark James Burge, Joshua C. Klontz, Richard W. Vorder Bruegge, and Anil K. Jain · 2012
Earlier work this paper cites.
How to do a structured literature review in computer science
Anders Kofod-Petersen · 2012
Earlier work this paper cites.
Exploring the boundaries of photo editing
Matthias Krug and Stefan Niggemeier · 2013
Earlier work this paper cites.
Discrimination in online ad delivery
Latanya Sweeney · 2013
Earlier work this paper cites.
Decaf: A deep convolutional activation feature for generic visual recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell · 2014
Earlier work this paper cites.
Age and gender estimation of unfiltered faces
Eran Eidinger, Roee Enbar, and Tal Hassner · 2014
Earlier work this paper cites.
Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, M. Maire, Serge J. Belongie, James Hays, P. Perona, D. Ramanan, Piotr Dollár, and C. L. Zitnick · 2014
Earlier work this paper cites.
Capturing long-tail distributions of object subcategories
Xiangxin Zhu, Dragomir Anguelov, and Deva Ramanan · 2014
Earlier work this paper cites.
Image retrieval using scene graphs
Justin Johnson, Ranjay Krishn, Micheal Stark, Li-Jia Li, Davod A. Shamma, Micheal S. Bernstein, and Li Fei-Fei · 2015
Earlier work this paper cites.
Unequal representation and gender stereotypes in image search results for occupations
Matthew Kay, Cynthia Matuszek, and Sean A. Munson · 2015
Earlier work this paper cites.
Pushing the frontiers of unconstrained face detection and recognition: Iarpa janus benchmark a
Brendan F. Klare, Ben Klein, Emma Taborsky, Austin Blanton, Jordan Cheney, Kristen Allen, Patrick Grother, Alan Mah, Mark Burge, and Anil J. Jain · 2015
Earlier work this paper cites.
Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey E. Hinton · 2015
Earlier work this paper cites.
Towards a learning theory of cause-effect inference
David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, and Ilya O. Tolstikhin · 2015
Earlier work this paper cites.
Comparison of data set bias in object recognition benchmarks
Ian Model and Lior Shamir · 2015
Earlier work this paper cites.
The uncomfortable truth about how we view working women, in one simple google search
Danielle Paquette · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Micheal Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
A deeper look at dataset bias
Tatiana Tommasi, Novi Patricia, Barbara Caputo, and Tinne Tuytelaars · 2015
Earlier work this paper cites.
Machine bias: There’s software used across the country to predict future criminals. and it’s biased against blacks
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016
Earlier work this paper cites.
Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, and Adam Kalai · 2016
Cited alongside, same era.
Inferring gender from names on the web: A comparative evaluation of gender detection methods
Fariba Karimi, Claudia Wagner, Florian Lemmerich, Mohsen Jadidi, and Markus Strohmaier · 2016
Cited alongside, same era.
Openimages: A public dataset for large-scale multi-label and multi-class image classification
Ivan Krasin, Tom Duerig, Neil Alldrin, Andreas Veit, Sami Abu-El-Haija, Serge Belongie, David Cai, Zheyun Feng, Vittorio Ferrari, Victor Gomes, Abhinav Gupta, Dhyanesh Narayanan, Chen Sun, Gal Chechik, and Kevin Murphy · 2016
Cited alongside, same era.
Building a large scale dataset for image emotion recognition: The fine print and the benchmark
Quanzeng You, Jiebo Luo, Hailin Jin, and Jianchao Yang · 2016
Cited alongside, same era.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan · 2017
Cited alongside, same era.
Learning to model and ignore dataset bias with mixed capacity ensembles
Christopher Clark, Mark Yatskar, and Luke Zettlemoyer · 2020
Later among the works it cites.
Demographic bias in biometrics: A survey on an emerging challenge
Pawel Drozdowski, Christian Rathgeb, Antitza Dantcheva, Naser Damer, and Christoph Busch · 2020
Later among the works it cites.
Investigating bias in deep face analysis: The kanface dataset and empirical study
Markos Georgopoulos, Yannis Panagakis, and Maja Pantic · 2020
Later among the works it cites.
Towards a critical race methodology in algorithmic fairness
Alex Hanna, Emily Denton, Andrew Smart, and Jamila Smith-Loud · 2020
Later among the works it cites.
Causal Inference: What If
Miguel A. Hernán and Jamie M. Robins · 2020
Later among the works it cites.
Wrongfully accused by an algorithm
Kashmir Hill · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova · 2017
Cited alongside, same era.
Inherent trade-offs in the fair determination of risk scores
Jon M. Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2017
Cited alongside, same era.
Discovering causal signals in images
David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Schölkopf, and Léon Bottou · 2017
Cited alongside, same era.
How do scholars approach the circular economy? a systematic literature review
Roberto Merli, Michele Preziosi, and Alessia Acampora · 2017
Cited alongside, same era.
No classification without representation: Assessing geodiversity issues in open data sets for the developing world
Shreya Shankar, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, and D. Sculley · 2017
Cited alongside, same era.
Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vincente Ordonez, and Kai-Wei Chang · 2017
Cited alongside, same era.
Places: A 10 million image database for scene recognition
Bolei Zhou, Agata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
Cited alongside, same era.
Crowdsourcing detection of sampling biases in image datasets
Xiao Hu, Haobo Wang, Anirudh Vegesana, Somesh Dube, Kaiwen Yu, Gore Kao, Shuo-Han Chen, Yung-Hsiang Lu, George K. Thiruvathukal, and Ming Yin · 2020
Later among the works it cites.
Identifying and correcting label bias in machine learning
Heinrich Jiang and Ofir Nachum · 2020
Later among the works it cites.
Applying fairness constraints on graph node ranks under personalization bias
Emmanouil Krasanakis, Symeon Papadopoulos, and Ioannis Kompatsiaris · 2020
Later among the works it cites.
Between subjectivity and imposition: Power dynamics in data annotation for computer vision
Milagros Miceli, Martin Schuessler, and Tianling Yang · 2020
Later among the works it cites.
Bias in data-driven artificial intelligence systems - an introductory survey
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, Ioannis Kompatsiaris, Katharina Kinder-Kurlanda, Claudia Wagner, Fariba Karimi, Miriam Fernández, Harith Alani, Bettina Berendt, Tina Kruegel, Christian Heinze, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis, and Steffen Staab · 2020
Later among the works it cites.
Large image datasets: A pyrrhic win for computer vision?
Vinay Uday Prabhu and Abeba Birhane · 2020
Later among the works it cites.
Face recognition: Too bias, or not too bias?
Joseph P. Robinson, Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner · 2020
Later among the works it cites.
Don’t judge an object by its context: Learning to overcome contextual bias
Krishna Kumar Singh, Dhruv Mahajan, Kristen Grauman, Yong Jae Lee, Matt Feiszli, and Deepti Ghadiyaram · 2020
Later among the works it cites.
Detect and correct bias in multi-site neuroimaging datasets
Christian Wachinger, Anna Rieckmann, and Sebastian Pölsterl · 2020
Later among the works it cites.
REVISE: A tool for measuring and mitigating bias in visual datasets
Angelina Wang, Arvind Narayanan, and Olga Russakovsky · 2020
Later among the works it cites.
Gender classification and bias mitigation in facial images
Wenying Wu, Pavlos Protopapas, Xheng Yang, and Panagiotis Michalatos · 2020
Later among the works it cites.
Towards fairer datasets: Filtering and balancing the distribution of the people subtree in the imagenet hierarchy
Kaiyu Yang, Klint Qinami, Li Fei-Fei, Jia Deng, and Olga Russakovsky · 2020
Later among the works it cites.
BDD100K: A diverse driving dataset for heterogeneous multitask learning
Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, and Trevor Darrell · 2020
Later among the works it cites.
Problematic machine behavior: A systematic literature review of algorithm audits
Jack Bandy · 2021
Closest in time.
Web futures: Inclusive, intelligent, sustainable the 2020 manifesto for web science (dagstuhl perspectives workshop 18262)
Bettina Berendt, Fabien Gandon, Susan Halford, Wendy Hall, Jim Hendler, Katharina E. Kinder-Kurlanda, Eirini Ntoutsi, and Steffen Staab · 2021
Closest in time.
An introduction to topological data analysis: Fundamental and practical aspects for data scientists
Frédéric Chazal and Bertrand Michel · 2021
Closest in time.
Yearbook photos of girls were altered to hide their chests
Maria Cramer and Micheal Levenson · 2021
Closest in time.
Towards measuring fairness in ai: the casual conversations dataset
Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, and Cristian Canton-Ferrer · 2021
Closest in time.
Measurement and fairness
Abigail Z. Jacobs and Hanna Wallach · 2021
Closest in time.
Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation
Kimmo Kärkkäinen and Jungseock Joo · 2021
Closest in time.
The use and misuse of counterfactuals in ethical machine learning
Atoosa Kasirzadeh and Andrew Smart · 2021
Closest in time.
Documenting computer vision datasets: An invitation to reflexive data practices
Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler, Dian Serbanescu, and Alex Hanna · 2021
Closest in time.
The creation and detection of deepfakes: A survey
Yisroel Mirsky and Wenke Lee · 2021
Closest in time.
Fairness in rankings and recommenders: Models, methods and research directions
Evaggelia Pitoura, Kostas Stefanidis, and Georgia Koutrika · 2021
Closest in time.
Image representations learned with unsupervised pre-training contain human-like biases
Ryan Steed and Aylin Caliskan · 2021
Closest in time.
Maad-face: A massively annotated attribute dataset for face images
Philipp Terhörst, Daniel Fährmann, Jan Niklas Kolf, Naser Damer, Florian Kirchbuchner, and Arjan Kuijper · 2021
Closest in time.
A comprehensive study on face recognition biases beyond demographics
Philipp Terhörst, Jan Niklas Kolf, Marco Huber, Florian Kirchbuchner, Naser Damer, Aythami Morales, Julian Fiérrez, and Arjan Kuijper · 2021
Closest in time.
Bag of tricks for long-tailed visual recognition with deep convolutional neural networks
Yongshun Zhang, Xiu-Shen Wei, Boyan Zhou, and Jianxin Wu · 2021
Closest in time.