Fetching the paper…
Reading the bibliography…
Few datasets contain self-identified sensitive attributes, inferring attributes risks introducing additional biases, and collecting attributes can carry legal risks.
On a measure of the information provided by an experiment
Dennis V Lindley · 1956
Earlier work this paper cites.
The influence of culture on visual perception
Marshall H Segall, Donald Thomas Campbell, and Melville Jean Herskovits · 1966
Earlier work this paper cites.
Seven strictures on similarity
Nelson Goodman · 1972
Earlier work this paper cites.
Natural categories
Eleanor H Rosch · 1973
Earlier work this paper cites.
Cognitive representations of semantic categories
Eleanor Rosch · 1975
Earlier work this paper cites.
The effect of context on the structure of categories
Emilie M Roth and Edward J Shoben · 1983
Earlier work this paper cites.
The instability of graded structure: Implications for the nature of concepts
Lawrence Barsalou · 1987
Earlier work this paper cites.
On the similarity of features
Benny Shanon · 1988
Earlier work this paper cites.
The view from nowhere
Thomas Nagel · 1989
Earlier work this paper cites.
Information-based objective functions for active data selection
David JC MacKay · 1992
Earlier work this paper cites.
Category labels and social reality: Do we view social categories as natural kinds?
Myron Rothbart and Marjorie Taylor · 1992
Earlier work this paper cites.
Respects for similarity
Douglas L Medin, Robert L Goldstone, and Dedre Gentner · 1993
Earlier work this paper cites.
Structural alignment in similarity and difference judgments
Arthur B Markman · 1996
Earlier work this paper cites.
Support vector machines
Marti A. Hearst, Susan T Dumais, Edgar Osuna, John Platt, and Bernhard Scholkopf · 1998
Earlier work this paper cites.
Nonintentional similarity processing
Arthur B Markman and Dedre Gentner · 2005
Earlier work this paper cites.
The implications of racial misclassification by observers
Mary E Campbell and Lisa Troyer · 2007
Earlier work this paper cites.
Labeled faces in the wild: A database forstudying face recognition in unconstrained environments
Gary B Huang, Marwan Mattar, Tamara Berg, and Eric Learned-Miller · 2008
Earlier work this paper cites.
Dlib-ml: A machine learning toolkit
Davis E King · 2009
Earlier work this paper cites.
Visual and semantic similarity in imagenet
Thomas Deselaers and Vittorio Ferrari · 2011
Earlier work this paper cites.
Looking the part: Social status cues shape race perception
Jonathan B Freeman, Andrew M Penner, Aliya Saperstein, Matthias Scheutz, and Nalini Ambady · 2011
Earlier work this paper cites.
Measuring diversity: the importance of species similarity
Tom Leinster and Christina A Cobbold · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
Learning face representation from scratch
Dong Yi, Zhen Lei, Shengcai Liao, and Stan Z Li · 2014
Earlier work this paper cites.
A study on different experimental configurations for age, race, and gender estimation problems
Pierluigi Carcagnì, Marco Del Coco, Dario Cazzato, Marco Leo, and Cosimo Distante · 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.
Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
Earlier work this paper cites.
The chicago face database: A free stimulus set of faces and norming data
Debbie S Ma, Joshua Correll, and Bernd Wittenbrink · 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, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Earlier work this paper cites.
Learning local feature descriptors with triplets and shallow convolutional neural networks
Vassileios Balntas, Edgar Riba, Daniel Ponsa, and Krystian Mikolajczyk · 2016
Earlier work this paper cites.
Shades of race: How phenotype and observer characteristics shape racial classification
Cynthia Feliciano · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
The multiple dimensions of race
Wendy D Roth · 2016
Cited alongside, same era.
Sphereface: Deep hypersphere embedding for face recognition
Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj, and Le Song · 2017
Cited alongside, same era.
Conditional similarity networks
Andreas Veit, Serge Belongie, and Theofanis Karaletsos · 2017
Cited alongside, same era.
Vggface2: A dataset for recognising faces across pose and age
Qiong Cao, Li Shen, Weidi Xie, Omkar M Parkhi, and Andrew Zisserman · 2018
Cited alongside, same era.
Diagnosing gender bias in image recognition systems
Carsten Schwemmer, Carly Knight, Emily D Bello-Pardo, Stan Oklobdzija, Martijn Schoonvelde, and Jeffrey W Lockhart · 2020
Later among the works it cites.
Revealing interpretable object representations from human behavior
Charles Y Zheng, Francisco Pereira, Chris I Baker, and Martin N Hebart · 2020
Later among the works it cites.
What we can’t measure, we can’t understand: Challenges to demographic data procurement in the pursuit of fairness
McKane Andrus, Elena Spitzer, Jeffrey Brown, and Alice Xiang · 2021
Later among the works it cites.
Pass: An imagenet replacement for self-supervised pretraining without humans
Yuki M Asano, Christian Rupprecht, Andrew Zisserman, and Andrea Vedaldi · 2021
Later among the works it cites.
Large image datasets: A pyrrhic win for computer vision?
Abeba Birhane and Vinay Uday Prabhu · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford · 2018
Cited alongside, same era.
The misgendering machines: Trans/hci implications of automatic gender recognition
Os Keyes · 2018
Cited alongside, same era.
Evaluating (and improving) the correspondence between deep neural networks and human representations
Joshua C Peterson, Joshua T Abbott, and Thomas L Griffiths · 2018
Cited alongside, same era.
Finding your lookalike: Measuring face similarity rather than face identity
Amir Sadovnik, Wassim Gharbi, Thanh Vu, and Andrew Gallagher · 2018
Cited alongside, same era.
Cosface: Large margin cosine loss for deep face recognition
Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou, Zhifeng Li, and Wei Liu · 2018
Cited alongside, same era.
A survey on facial soft biometrics for video surveillance and forensic applications
Fabiola Becerra-Riera, Annette Morales-González, and Heydi Méndez-Vázquez · 2019
Cited alongside, same era.
Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Later among the works it cites.
Understanding and mitigating annotation bias in facial expression recognition
Yunliang Chen and Jungseock Joo · 2021
Later among the works it cites.
Emily Denton, Mark Díaz, Ian Kivlichan, Vinodkumar Prabhakaran, and Rachel Rosen · 2021
Later among the works it cites.
Towards measuring fairness in ai: the casual conversations dataset
Caner Hazirbas, Joanna Bitton, Brian Dolhansky, Jacqueline Pan, Albert Gordo, and Cristian Canton Ferrer · 2021
Later among the works it cites.
Emergent dimensions underlying human perception of the reachable world
Emilie L Josephs, Martin N Hebart, and Talia Konkle · 2021
Later among the works it cites.
Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation
Kimmo Karkkainen and Jungseock Joo · 2021
Later among the works it cites.
Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
Later among the works it cites.
Reduced, reused and recycled: The life of a dataset in machine learning research
Bernard Koch, Emily Denton, Alex Hanna, and Jacob Gates Foster · 2021
Later among the works it cites.
Udis: Unsupervised discovery of bias in deep visual recognition models
Arvindkumar Krishnakumar, Viraj Prabhu, Sruthi Sudhakar, and Judy Hoffman · 2021
Later among the works it cites.
The india face set: International and cultural boundaries impact face impressions and perceptions of category membership
Anjana Lakshmi, Bernd Wittenbrink, Joshua Correll, and Debbie S Ma · 2021
Later among the works it cites.
Similarity as a window on the dimensions of object representation
Bradley C Love and Brett D Roads · 2021
Later among the works it cites.
Chicago face database: Multiracial expansion
Debbie S Ma, Justin Kantner, and Bernd Wittenbrink · 2021
Later among the works it cites.
Identical twins as a facial similarity benchmark for human facial recognition
John McCauley, Sobhan Soleymani, Brady Williams, John Dando, Nasser Nasrabadi, and Jeremy Dawson · 2021
Later among the works it cites.
Enriching imagenet with human similarity judgments and psychological embeddings
Brett D Roads and Bradley C Love · 2021
Later among the works it cites.
Do datasets have politics? disciplinary values in computer vision dataset development
Morgan Klaus Scheuerman, Alex Hanna, and Emily Denton · 2021
Later among the works it cites.
A step toward more inclusive people annotations for fairness
Candice Schumann, Susanna Ricco, Utsav Prabhu, Vittorio Ferrari, and Caroline Rebecca Pantofaru · 2021
Later among the works it cites.
Exploring perceived face similarity and its relation to image-based spaces: an effect of familiarity
Rosyl S Somai and Peter JB Hancock · 2021
Later among the works it cites.
Image representations learned with unsupervised pre-training contain human-like biases
Ryan Steed and Aylin Caliskan · 2021
Later among the works it cites.
Understanding and evaluating racial biases in image captioning
Dora Zhao, Angelina Wang, and Olga Russakovsky · 2021
Later among the works it cites.
A data-driven investigation of human action representations
Diana C Dima, Martin N Hebart, and Leyla Isik · 2022
Later among the works it cites.
Vision models are more robust and fair when pretrained on uncurated images without supervision
Priya Goyal, Quentin Duval, Isaac Seessel, Mathilde Caron, Mannat Singh, Ishan Misra, Levent Sagun, Armand Joulin, and Piotr Bojanowski · 2022
Later among the works it cites.
Things-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior
Martin N Hebart, Oliver Contier, Lina Teichmann, Adam Rockter, Charles Y Zheng, Alexis Kidder, Anna Corriveau, Maryam Vaziri-Pashkam, and Chris I Baker · 2022
Later among the works it cites.
A study of face obfuscation in imagenet
Kaiyu Yang, Jacqueline H Yau, Li Fei-Fei, Jia Deng, and Olga Russakovsky · 2022
Later among the works it cites.
Ethical considerations for collecting human-centric image datasets
Jerone TA Andrews, Dora Zhao, William Thong, Apostolos Modas, Orestis Papakyriakopoulos, Shruti Nagpal, and Alice Xiang · 2023
Closest in time.