Image Datasets

This theme draws from Data / Set / Match, a programme of commissions and research at The Photographers' Gallery that sought new ways to present, visualise and interrogate contemporary image datasets. The essays and artworks here draw attention to, and explore, the uses, influence and politics around image datasets and contemporary visual culture.

A publication that critically investigates the development and impact of visual datasets from the perspective of machine learning, while exploring their artistic possibilities in the contemporary image culture.
I proposed what would become Lacework in the Summer of 2019. In my proposal, I describe a cycle of videos curated from MIT's 'Moments In Time' dataset, each then slowed down, interpolated, and upscaled immensely into imagined detail, one flowing into another like a river...
I write this from my small New York apartment in my fourth month of isolation. The pandemic has required each of us to slow down and do less, and I keep thinking of a childhood friend who once told me, “We’re human beings, not human doings”. Even as a teenager, I knew this was an important paradigm shift: it meant that we could rethink how we …
Lacework is a new work by Everest Pipkin that uses artificial neural networks to reinscribe the videos of MIT’s Moments in Time Dataset.
This article weaves a thread between two commissions, historically through Virginia Woolf, technologically by computational juxtaposition, as well as poetically in the viewer’s experience through a speculative remix.
A speculative remix that confronts Epic Kitchens, a dataset of first-person cooking videos, with quotations from literature written during or about prior pandemics such as the bubonic plague and the global influenza pandemic of 1918-19.
This article is an overview of the projects 'Epic Handwashing in a Time of Lost Narratives' and 'A Kitchen of One's Own' weaving a thread between the technical and the conceptual: the projects are linked historically by the writing and arguments put forth by Virginia Woolf, technologically by computational juxtapositions of text and image, as well …
Philipp Schmitt's 'Declassifier' uses a computer vision algorithm trained on COCO, an image dataset developed by Microsoft in 2014.
The Future Is Here!, the title of Mimi Onuoha’s video project reflecting the human side of crowdsourced image labelling, is spot on. The stories I have been told by crowd workers from across the globe doing this work full-time indeed often have an eerily Gibsonian ring to them. Especially the stories from Venezuela.
I met with Kate Crawford and Trevor Paglen on the press preview of their exhibition Training Humans in Milan at Osservatorio Prada. It was the morning of September 11th –not a neutral day to unthink photography and the power operations of vast populations of images. On the contrary, it was the most apt one to seriously consider Crawford and …
In Heather Dewey-Hagborg’s artwork ‘How do you see me?’, commissioned for the Data/Set/Match programme at The Photographers’ Gallery, the artist explores how machines see us. A question that has been carefully slipping through several areas of production and research during the past couple of decades. At the same time an essential need has also …
In September 2019 the ImageNet creator Fei-Fei Li gave a talk at The Photographers' Gallery talking through the events and key people that led to the creation of visual datasets.
In 2019 The Photographers' Gallery digital programme launched 'Data / Set / Match', a year-long programme that explores new ways to present, visualise and interrogate contemporary image datasets. This introductory essay presents some key concepts and questions that make the computer vision dataset an object of concern for artists, photographers, …