Pub Date : 2023-08-09DOI: 10.1080/17540763.2023.2235361
Conohar Scott
La Vetta e L’Abisso is a sequence of photographs which address the problems associated with over-mining in the famous white marble mines of Carrara, Tuscany. As a visual essay, the series attempts to undercut contemporary notions of the sublime in the documentation of mineral extractivism, which has been dominant in recent years due to the popularity of photographers such as Edward Burtynsky. Furthermore, the title of the essay, and the display of the monochrome large format photographs with the addition of a gold-selenium tone, alludes to eco-Marxist notions of commodity fetishism and social alienation, which underpin the exploitative logic of capitalist (re-)production. Drawing on the authors previously published critical commentaries on the qualities of photography and environmental activism, this essay proposes an approach to praxis which undercuts the distant passivity of the sublime in favour of encountering the negative effects of extractivism first-hand.
La Vetta e L’Abisso是一系列照片，旨在解决托斯卡纳卡拉拉著名汉白玉矿过度开采的问题。作为一篇视觉散文，该系列试图在矿物提取主义的文献中削弱当代崇高的概念，近年来，由于爱德华·伯廷斯基等摄影师的流行，矿物提取主义一直占据主导地位。此外，这篇文章的标题，以及添加了金硒色调的单色大幅面照片的展示，暗示了生态马克思主义的商品恋物癖和社会异化观念，这些观念支撑着资本主义（再）生产的剥削逻辑。本文借鉴了作者之前发表的关于摄影和环境激进主义品质的评论，提出了一种实践的方法，这种方法削弱了崇高的遥远被动性，有利于直接遭遇提取主义的负面影响。
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Pub Date : 2023-08-09DOI: 10.1080/17540763.2023.2227653
Claudia Arozqueta
This article examines how Mexican artist Daniela Edburg has been using Gothic idioms to raise awareness of both personal and environmental ailments. For over two decades, Edburg has combined digital photography and textiles to create fictional settings in which women are depicted in domestic spaces or natural landscapes in bizarre situations. Some of her characters are attacked by monsters, while others appear in a state of escapism, and many have encounters with death or disease. In this paper, I examine the connections between Edburg’s art and Gothic tropes including the uncanny, the return of the dead, madness and disease, intrusions into domestic space, the clash of old and new, and the yearning for reconnection with nature. The text begins with an analysis of her most recent project, Malaise, which alludes to Frankenstein and crystallizes core concerns that have persisted throughout her career. Later, I examine prior series by the artist to demonstrate how gothic traits have always been present in Edburg’s work. Using a gothic style, the artist has constantly reflected on how humans relate to the natural world through the artificial, as well as the consequences of this attitude toward life, which has led us to a dystopian future.
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Pub Date : 2023-08-09DOI: 10.1080/17540763.2023.2237966
Meghan L. E. Kirkwood
This paper examines the work of three contemporary South African photographers whose adaptations of landscape photography support inquiry into themes such as agency, identity, and belonging. None of these artists self-identifies as a landscape photographer, but each has taken up the genre to address topics of social concern such as: colonialism, under-documented histories, and the geographical imagination. Jean Brundrit adapts high-resolution survey technology to chart waves; Cedric Nunn creates extended captions to reorient views of the modern Eastern Cape landscape in relation to Xhosa history; and Francki Burger layers negatives in the darkroom to construct ethereal environments that examine emotive connections to land. These artists draw upon photographic techniques that may be considered ‘alternative’ in relation to traditional modes of landscape photography. In doing so, they challenge, reinterpret, and expand the definition of what constitutes a landscape image and landscape photography. Further, their respective works offer insight into the evolution of the genre from its nineteenth and early twentieth century applications in South Africa, as well as its utility for socially-concerned artists in the post-apartheid era.
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Pub Date : 2023-05-04DOI: 10.1080/17540763.2023.2189158
A. Wasielewski
Deep learning techniques are increasingly used to automate categorization and identification tasks for large datasets of digital photographs. For rasterized images formats, such as JPEGs, GIFs, and PNGs, the analysis happens on the level of individual pixels. Given this, digital images used in deep learning applications are typically restricted to relatively low-resolution formats to conform to the standards of popular pre-trained neural networks. Using Hito Steyerl’s conception of the ‘poor image’ as a theoretical frame, this article investigates the use of these relatively low-resolution images in automated analysis, exploring the ways in which they may be deemed preferable to higher-resolution images for deep learning applications. The poor image is rich in value in this context, as it limits the undesirable ‘noise’ of too much detail. In considering the case of automated art authentication, this article argues that a notion of authenticity is beginning to emerge that raises questions around Walter Benjamin’s often-cited definition in relation to mass image culture. Copies or reproductions are now forming the basis for a new model of authenticity, which exists latently in the formal properties of a digital image.
{"title":"AUTHENTICITY AND THE POOR IMAGE IN THE AGE OF DEEP LEARNING","authors":"A. Wasielewski","doi":"10.1080/17540763.2023.2189158","DOIUrl":"https://doi.org/10.1080/17540763.2023.2189158","url":null,"abstract":"Deep learning techniques are increasingly used to automate categorization and identification tasks for large datasets of digital photographs. For rasterized images formats, such as JPEGs, GIFs, and PNGs, the analysis happens on the level of individual pixels. Given this, digital images used in deep learning applications are typically restricted to relatively low-resolution formats to conform to the standards of popular pre-trained neural networks. Using Hito Steyerl’s conception of the ‘poor image’ as a theoretical frame, this article investigates the use of these relatively low-resolution images in automated analysis, exploring the ways in which they may be deemed preferable to higher-resolution images for deep learning applications. The poor image is rich in value in this context, as it limits the undesirable ‘noise’ of too much detail. In considering the case of automated art authentication, this article argues that a notion of authenticity is beginning to emerge that raises questions around Walter Benjamin’s often-cited definition in relation to mass image culture. Copies or reproductions are now forming the basis for a new model of authenticity, which exists latently in the formal properties of a digital image.","PeriodicalId":39970,"journal":{"name":"Photographies","volume":"16 1","pages":"191 - 210"},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44750124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-04DOI: 10.1080/17540763.2023.2189159
N. Malevé
Computer vision datasets have proved to be key instruments to interpret visual data. This article concentrates on benchmark datasets which are used to define a technical problem and provide with a common referent against which different solutions can be compared. Through three case studies, ImageNet, the Pilot Parliaments Benchmark dataset and VizWiz, the article analyzes how photography is mobilised to conceive interventions in computer vision. The benchmark is a privileged site where photographic curation is tactically performed to change the scale of visual perception, oppose racial and gendered discrimination or rethink image interpretation for visually impaired users. Through the elaboration of benchmarks, engineers create curatorial pipelines involving large chains of heterogeneous actors exploiting various photographic practices from amateur snapshot to political portraiture or photography made by blind users. The article contends that the mobilisation of photography in the benchmark goes together with a multifaceted notion of vulnerability. It analyzes how various forms of vulnerabilities and insecurities pertaining to users, software companies, or vision systems are framed and how benchmarks are conceived in response to them. Following the alliances that form around vulnerabilities, the text explores the potential and limits of the practices of benchmarking in computer vision.
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Pub Date : 2023-05-04DOI: 10.1080/17540763.2023.2189286
Emily Pugh, Tracy Stuber
This paper analyzes the relationship between photography and machine vision by examining its prehistory, as embodied in the art-historical photo archive. It characterizes the introduction of machine vision to the world of libraries, archives, and museums as a renewed (rather than wholly new) effort to mechanize or systematize art and its history. Assumptions and attitudes about photography embedded in the photo archive are therefore easily and often inconspicuously reproduced in efforts to study art computationally. Noting this repetition, this paper reframes the debate about art-historical applications of computer vision to emphasize the issues this technology raises about what constitutes art-historical work. The question is not whether we should use computer vision or computers for art-historical inquiry, but rather, what kinds of activities we ask computers to perform. Understanding machine vision in the context of its prehistory is critical for explicating its relationship to photography, and the role of photography and digital images in the study of visual culture more generally.
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Pub Date : 2023-05-04DOI: 10.1080/17540763.2023.2189285
Gabriel Pereira, Bruno Moreschi
The emergence of contemporary computer vision coincides with the growth and dissemination of large-scale image data sets. The grandeur of such image collections has raised fascination and concern. This article critically interrogates the assumption of scale in computer vision by asking: What can be gained by scaling down and living with images from large-scale data sets? We present results from a practice-based methodology: an ongoing exchange of individual images from data sets with selected participants. The results of this empirical inquiry help to consider how a durational engagement with such images elicits profound and variously situated meanings beyond the apparent visual content used by algorithms. We adopt the lens of critical pedagogy to untangle the role of data sets in teaching and learning, thus raising two discussion points: First, regarding how the focus on scale ignores the complexity and situatedness of images, and what it would mean for algorithms to embed more reflexive ways of seeing; Second, concerning how scaling down may support a critical literacy around data sets, raising critical consciousness around computer vision. To support the dissemination of this practice and the critical development of algorithms, we have produced a teaching plan and a tool for classroom use.
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Pub Date : 2023-05-04DOI: 10.1080/17540763.2023.2194878
Doron Altaratz
How can professional photography continue to exist in an age of machine vision? As this article suggests, computational photography destabilizes the ideology of professional photographic distinctiveness, expertise, agency and creativity. In an era characterized by constant instability due to technological developments, changes to photographer’s professional habitus are expected. While these changes are connected to technical modifications in professional tools, they can deeply challenge the identities of practitioners, their perception of photography’s fluctuating affordances, their own roles in image-production, and even the distinctiveness of the medium itself. Professional photography is thus a powerful signifier of the photographic medium and a key arena for understanding the social meaning of the automation of vision across the entire photographic field. Drawing upon interviews with professional photographers who use Structure from Motion, this article propose a new emerging professional identity adapted to this situation: ‘the computational photographer’. For such a photographer the automation of photographic processes necessitates a shift in the site of identity-construction and expertise, away from image-production itself and towards the sphere of distribution on professionally oriented digital platforms. I argue that the advent of the 'computational photographer' indicates that automation processes and practices of technological embodiment influence the habitus of professional photographers.
在机器视觉时代，专业摄影如何继续存在?正如本文所指出的，计算机摄影动摇了专业摄影的独特性、专业知识、代理和创造力的意识形态。在一个因技术发展而不断不稳定的时代，摄影师的职业习惯的变化是值得期待的。虽然这些变化与专业工具的技术改进有关，但它们可以深刻地挑战从业者的身份，他们对摄影波动性的感知，他们在图像制作中的角色，甚至是媒介本身的独特性。因此，专业摄影是摄影媒介的强大象征，也是理解整个摄影领域视觉自动化的社会意义的关键舞台。通过对使用Structure from Motion的专业摄影师的采访，本文提出了一种适应这种情况的新兴职业身份:“计算摄影师”。对于这样一个摄影师来说，摄影过程的自动化需要身份建构和专业知识的转移，从图像生产本身转向以专业为导向的数字平台上的传播领域。我认为，“计算摄影师”的出现表明，自动化过程和技术具体化的实践影响了专业摄影师的习惯。
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Pub Date : 2023-05-04DOI: 10.1080/17540763.2023.2189287
M. Hand, Ashley Scarlett
The development and refinement of contemporary machine vision technologies has relied centrally on the volume of photographic images uploaded, labeled, and circulated online. These images have provided the foundational data, and in some cases have solicited the human labour, required to develop sophisticated techniques for automated object recognition, image classification, and semantic segmentation. Reciprocally, machine vision is also transforming established ways of thinking about and practicing photography, by enabling new forms of image analysis, manipulation, and creation, and expanding formulations and applications of the ‘photographic’ image. This special issue of photographies is devoted to an examination of how photography is reshaping machine vision, and how machine vision is reshaping photography. Bringing together grounded studies and critical engagements with existing scholarship, each article examines the means through which photographic images and practices are being put to use in advancing the aims and potential applications of machine vision. In so doing, they leverage the photographic — broadly conceived — to develop greater insight into the emerging politics and practices of computational seeing. In what follows, we offer a brief consideration of emergent and historical convergences of machine vision and photography followed by a sweeping review of recent photographic discourse that contends with the contemporary media situation. Drawing these discussions together, we suggest key thematic areas of analysis that have begun to define critical engagement with the intersection of photography and machine vision, indicating how the articles in this special issue contribute to these developing discourses.
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