Fetching the paper…
Reading the bibliography…
Current perceptual similarity metrics operate at the level of pixels and patches.
A sequential theory of psychological discrimination
S. W. Link and R. A. Heath · 1975
Earlier work this paper cites.
Effects of perceptual and conceptual similarity in semantic priming
Robert Schreuder, Giovanni B Flores d’Arcais, and Ge Glazenborg · 1984
Earlier work this paper cites.
Color indexing
Michael J Swain and Dana H Ballard · 1991
Earlier work this paper cites.
Serial retrieval processes in the recovery of order information
Brian McElree and Barbara A. Dosher · 1993
Earlier work this paper cites.
Respects for similarity
Doug Medin, Robert Goldstone, and Dedre Gentner · 1993
Earlier work this paper cites.
The cognitive impenetrability of cognition
Patrick Cavanagh · 1999
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew Zisserman · 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.
Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
Earlier work this paper cites.
Complex wavelet structural similarity: A new image similarity index
Mehul P Sampat, Zhou Wang, Shalini Gupta, Alan Conrad Bovik, and Mia K Markey · 2009
Earlier work this paper cites.
Large scale online learning of image similarity through ranking
Gal Chechik, Varun Sharma, Uri Shalit, and Samy Bengio · 2010
Earlier work this paper cites.
Sun database: Large-scale scene recognition from abbey to zoo
Jianxiong Xiao, James Hays, Krista A Ehinger, Aude Oliva, and Antonio Torralba · 2010
Earlier work this paper cites.
Hdr-vdp-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions
Rafał Mantiuk, Kil Joong Kim, Allan G Rempel, and Wolfgang Heidrich · 2011
Earlier work this paper cites.
What is it like to be a newborn?
Philippe Rochat · 2011
Earlier work this paper cites.
Fsim: A feature similarity index for image quality assessment
Lin Zhang, Lei Zhang, Xuanqin Mou, and David Zhang · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton · 2012
Earlier work this paper cites.
Cognitive penetrability of perception
Dustin Stokes · 2013
Earlier work this paper cites.
Food-101–mining discriminative components with random forests
Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool · 2014
Earlier work this paper cites.
Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 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.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Signal Processing: Image Communication
Image database tid2013: Peculiarities, results and perspectives · 2015
Earlier work this paper cites.
Using psychophysics to ask if the brain samples or maximizes
Daniel E. Acuna, Max Berniker, Hugo L. Fernandes, and Konrad P. Kording · 2015
Earlier work this paper cites.
Texture synthesis using convolutional neural networks
Leon Gatys, Alexander S Ecker, and Matthias Bethge · 2015
Earlier work this paper cites.
A neural algorithm of artistic style
Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2015
Earlier work this paper cites.
Geodesics of learned representations
Olivier J Hénaff and Eero P Simoncelli · 2015
Earlier work this paper cites.
Understanding deep image representations by inverting them
Aravindh Mahendran and Andrea Vedaldi · 2015
Earlier work this paper cites.
Image database tid2013
Nikolay Ponomarenko, Lina Jin, Oleg Ieremeiev, Vladimir Lukin, Karen Egiazarian, Jaakko Astola, Benoit Vozel, Kacem Chehdi, Marco Carli, Federica Battisti, and C.-C. Jay Kuo · 2015
Earlier work this paper cites.
Generating images with perceptual similarity metrics based on deep networks
Alexey Dosovitskiy and Thomas Brox · 2016
Earlier work this paper cites.
Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
Earlier work this paper cites.
The sketchy database: Learning to retrieve badly drawn bunnies
Patsorn Sangkloy, Nathan Burnell, Cusuh Ham, and James Hays · 2016
Cited alongside, same era.
Cognitive Impenetrability
Michael R.W. Dawson · 2017
Cited alongside, same era.
Feature visualization
Chris Olah, Alexander Mordvintsev, and Ludwig Schubert · 2017
Cited alongside, same era.
Learning from simulated and unsupervised images through adversarial training
Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, and Russell Webb · 2017
Cited alongside, same era.
Conditional similarity networks
Andreas Veit, Serge Belongie, and Theofanis Karaletsos · 2017
Cited alongside, same era.
Pieapp: Perceptual image-error assessment through pairwise preference
Ekta Prashnani, Hong Cai, Yasamin Mostofi, and Pradeep Sen · 2018
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Later among the works it cites.
Masked autoencoders are scalable vision learners, 2021
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2021
Later among the works it cites.
The many faces of robustness: A critical analysis of out-of-distribution generalization
Dan Hendrycks, Steven Basart, Norman Mu, Saurav Kadavath, Frank Wang, Evan Dorundo, Rahul Desai, Tyler Zhu, Samyak Parajuli, Mike Guo, Dawn Song, Jacob Steinhardt, and Justin Gilmer · 2021
Later among the works it cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
Later among the works it cites.
Openclip, July 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 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…
Deep image prior
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2018
Cited alongside, same era.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Cited alongside, same era.
Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Andrei Barbu, David Mayo, Julian Alverio, William Luo, Christopher Wang, Dan Gutfreund, Josh Tenenbaum, and Boris Katz · 2019
Cited alongside, same era.
Things: A database of 1,854 object concepts and more than 26,000 naturalistic object images
Martin N Hebart, Adam H Dickter, Alexis Kidder, Wan Y Kwok, Anna Corriveau, Caitlin Van Wicklin, and Chris I Baker · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Cited alongside, same era.
E-lpips: robust perceptual image similarity via random transformation ensembles
Markus Kettunen, Erik Härkönen, and Jaakko Lehtinen · 2019
Cited alongside, same era.
Putting nerf on a diet: Semantically consistent few-shot view synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
Later among the works it cites.
Cdpam: Contrastive learning for perceptual audio similarity
Pranay Manocha, Zeyu Jin, Richard Zhang, and Adam Finkelstein · 2021
Later among the works it cites.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Later among the works it cites.
Stylespace analysis: Disentangled controls for stylegan image generation
Zongze Wu, Dani Lischinski, and Eli Shechtman · 2021
Later among the works it cites.
Learning to generate line drawings that convey geometry and semantics
Caroline Chan, Frédo Durand, and Phillip Isola · 2022
Later among the works it cites.
Reproducible scaling laws for contrastive language-image learning
Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev · 2022
Later among the works it cites.
k-diffusion
Katherine Crowson · 2022
Later among the works it cites.
Is synthetic data from generative models ready for image recognition?
Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip H. S. Torr, Song Bai, and Xiaojuan Qi · 2022
Later among the works it cites.
Zero-shot text-guided object generation with dream fields
Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, and Ben Poole · 2022
Later among the works it cites.
Do better imagenet classifiers assess perceptual similarity better?
Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, and Ekin Dogus Cubuk · 2022
Later among the works it cites.
Clip guided diffusion
Clay Mullis · 2022
Later among the works it cites.
Human alignment of neural network representations
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A Vandermeulen, and Simon Kornblith · 2022
Later among the works it cites.
Gan-supervised dense visual alignment
William Peebles, Jun-Yan Zhu, Richard Zhang, Antonio Torralba, Alexei A Efros, and Eli Shechtman · 2022
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
Later among the works it cites.
Fake it till you make it: Learning transferable representations from synthetic imagenet clones
Mert Bulent Sariyildiz, Alahari Karteek, Diane Larlus, and Yannis Kalantidis · 2022
Later among the works it cites.
Splicing vit features for semantic appearance transfer
Narek Tumanyan, Omer Bar-Tal, Shai Bagon, and Tali Dekel · 2022
Later among the works it cites.
Clipasso: Semantically-aware object sketching
Yael Vinker, Ehsan Pajouheshgar, Jessica Y Bo, Roman Christian Bachmann, Amit Haim Bermano, Daniel Cohen-Or, Amir Zamir, and Ariel Shamir · 2022
Later among the works it cites.
Synthetic data from diffusion models improves imagenet classification
Shekoofeh Azizi, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi, and David J. Fleet · 2023
Closest in time.
Instructpix2pix: Learning to follow image editing instructions, 2023
Tim Brooks, Aleksander Holynski, and Alexei A. Efros · 2023
Closest in time.
Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T Freeman, Michael Rubinstein, et al · 2023
Closest in time.
Scaling vision transformers to 22 billion parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, et al · 2023
Closest in time.
Things-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior
Martin N Hebart, Oliver Contier, Lina Teichmann, Adam H Rockter, Charles Y Zheng, Alexis Kidder, Anna Corriveau, Maryam Vaziri-Pashkam, and Chris I Baker · 2023
Closest in time.