Processing and acquisition traces in visual encoders: What does CLIP know about your camera?

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00388306" target="_blank" >RIV/68407700:21230/25:00388306 - isvavai.cz</a>

Result on the web

<a href="https://openaccess.thecvf.com/content/ICCV2025/papers/Ramos_Processing_and_acquisition_traces_in_visual_encoders_What_does_CLIP_ICCV_2025_paper.pdf" target="_blank" >https://openaccess.thecvf.com/content/ICCV2025/papers/Ramos_Processing_and_acquisition_traces_in_visual_encoders_What_does_CLIP_ICCV_2025_paper.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Processing and acquisition traces in visual encoders: What does CLIP know about your camera?

Original language description

Prior work has analyzed the robustness of visual encoders to image transformations and corruptions, particularly in cases where such alterations are not seen during training. When this occurs, they introduce a form of distribution shift at test time, often leading to performance degradation. The primary focus has been on severe corruptions that, when applied aggressively, distort useful signals necessary for accurate semantic predictions. We take a different perspective by analyzing parameters of the image acquisition process and transformations that may be subtle or even imperceptible to the human eye. We find that such parameters are systematically encoded in the learned visual representations and can be easily recovered. More strikingly, their presence can have a profound impact, either positively or negatively, on semantic predictions. This effect depends on whether there is a strong correlation or anti-correlation between semantic labels and these acquisition-based or processing-based labels. Our code and data are available at: https://github.com/ryan-caesar-ramos/visual-encoder-traces

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GM21-28830M" target="_blank" >GM21-28830M: Learning Universal Visual Representation with Limited Supervision</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

ICCV2025: Proceedings of the International Conference on Computer Vision

ISBN

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ISSN

1550-5499

e-ISSN

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Number of pages

11

Pages from-to

17056-17066

Publisher name

IEEE Communications Society

Place of publication

Anchorage

Event location

Honolulu

Event date

Oct 19, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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