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Original w:light stage used in the 1999 reflectance capture by w:Paul Debevec et al at the w:University of Southern California.

It consists of two w:rotary axes with w:height and w:radius control. A w:light source and a w:polarizer in front of the light source were placed on one arm and a camera and the other polarizer on the other arm. See picture below, for what they did to the captured reflection.

Original image by Debevec et al. – Copyright ACM 2000 – https://dl.acm.org/citation.cfm?doid=311779.344855 – Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.


Image 1: Separating specular and diffuse reflected light

(a) Normal image in dot lighting

(b) Image of the diffuse reflection which is caught by placing a vertical polarizer in front of the light source and a horizontal in the front the camera

(c) Image of the highlight specular reflection which is caught by placing both polarizers vertically

(d) Subtraction of c from b, which yields the specular component

Images are scaled to seem to be the same luminosity.

Original image by Debevec et al. – Copyright ACM 2000 – https://dl.acm.org/citation.cfm?doid=311779.344855 – Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.


When the camera does not exist, but the subject being imaged with a simulation of a (movie) camera deceives the watcher to believe it is some living or dead person it is a digital look-alike.

In 2017-2018 this started to be referred to as w:deepfake, even though altering video footage of humans with a computer with a deceiving effect is actually 20 yrs older than the name "deep fakes" or "deepfakes".[1][2]

When it cannot be determined by human testing or media forensics whether some fake voice is a synthetic fake of some person's voice, or is it an actual recording made of that person's actual real voice, it is a pre-recorded digital sound-alike. This is now commonly referred to as w:audio deepfake.

Real-time digital look-and-sound-alike in a video call was used to defraud a substantial amount of money in 2023.[3]

Welcome to Stop Synthetic Filth! wiki, an open w:non-profit w:copylefted w:public service announcement wiki that contains no pornography and that anybody with a computer can edit anonymously or with a free account available upon reasonable request.

This is wiki is about discovering ways of stopping and minimizing the damage from synthetic human-like fakes i.e naked digital look-alikes and clothed digital sound-alikes that result from covert modeling i.e. thieving of the human appearance and of the naked human voice.

Adequate Porn Watcher AI (concept) #SSF! wiki proposed countermeasure to synthetic porn: Adequate Porn Watcher AI is a 2019 concept for an AI to protect the humans against synthetic filth attacks by looking for porn that should not be.

How to protect yourself and others from covert modeling

Biblical explanation - The books of Daniel and Revelation, wherein Daniel 7 and Revelation 13 we are warned of this age of industrial filth, is for those who believe in Jesus. We have a list of list of Bibles and churches‎ if you want to join in studying and spreading the word against the beasts.

Current and possible laws and their application | Mediatheque | Glossary | Resources | Marketing against synthetic filth | Quotes | Atheist explanation | About this wiki | Scratchpad for quick drafting, sandbox if you want to try editing.

Currently it is week #13 and today is Thursday 28 March 2024 and this wiki has 23 articles with 4,427 edits. 105 files have been uploaded.


Synopses of SSF! wiki in other languages in wordpress

The domain Stop-Synthetic-Filth-org-icon.pngstop-synthetic-filth.org is currently registered until Saturday 2028-01-15 (check) and the registration will be extended as long as needed.

#SSF!'s predecessor domain is BCM-logo-favicon-ico-C!.png Ban-Covert-Modeling.org #BCM!. It will expire on Wednesday 2029-03-14 (check), unless renewed.

Get in touch

Introduction Since the early 00's it has become (nearly) impossible to determine in still or moving pictures what is an image of a human, imaged with a (movie) camera and what on the other hand is a simulation of an image of a human imaged with a simulation of a camera. When there is no camera and the target being imaged with a simulation looks deceptively like some real human, dead or living, it is a digital look-alike.

Now in the late 2010's the equivalent thing is happening to our voices i.e. they can be stolen to some extent with the 2016 prototypes like w:Adobe Inc.'s w:Adobe Voco and w:Google's w:DeepMind w:WaveNet and made to say anything. When it is not possible to determine with human testing or testing with technological means what is a recording of some living or dead person's real voice and what is a simulation it is a digital sound-alike. 2018 saw the publication of Google Research's sound-like-anyone machine 'Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis' at the w:NeurIPS conference and by the end of 2019 Symantec research had learned of 3 cases where digital sound-alike technology had been used for crimes.[4]


Then in 2018 at the w:Conference on Neural Information Processing Systems (NeurIPS) the work 'Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis' (at arXiv.org) was presented. The pre-trained model is able to steal voices from a sample of only 5 seconds with almost convincing results

The Iframe below is transcluded from 'Audio samples from "Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis"' at google.gituhub.io, the audio samples of a sound-like-anyone machine presented as at the 2018 w:NeurIPS conference by Google researchers.

Have a listen.

Observe how good the "VCTK p240" system is at deceiving to think that it is a person that is doing the talking.


Therefore it is high time to act and to ban unauthorized synthetic pornography, build the Adequate Porn Watcher AI (concept) to protect humanity from visual synthetic filth and to criminalize covert modeling of the naked human voice and synthesis from a covert voice model!

Covert modeling poses growing threats to

  1. The right to be the only one that looks like me (compromised by digital look-alikes)
  2. The right to be the only one able to make recordings that sound like me (compromised by digital sound-alikes)

And these developments have various severe effects on the right to privacy, provability by audio and video evidence and deniability.

Thank yous for tech


Stop Synthetic Filth! wiki is an open w:non-profit w:copylefted w:public service announcement by User:Juho Kunsola (website) served from Finland and hosted at a hosting business that uses electricity from renewable sources only. (Check)

References

  1. Boháček, Matyáš; Farid, Hany (2022-11-23). "Protecting world leaders against deep fakes using facial, gestural, and vocal mannerisms". w:Proceedings of the National Academy of Sciences of the United States of America. 119 (48). doi:10.1073/pnas.221603511. Retrieved 2023-01-05.
  2. Bregler, Christoph; Covell, Michele; Slaney, Malcolm (1997-08-03). "Video Rewrite: Driving Visual Speech with Audio" (PDF). SIGGRAPH '97: Proceedings of the 24th annual conference on Computer graphics and interactive techniques: 353–360. doi:10.1145/258734.258880. Retrieved 2022-09-09.
  3. "'Deepfake' scam in China fans worries over AI-driven fraud". w:Reuters.com. w:Reuters. 2023-05-22. Retrieved 2023-06-05.
  4. Drew, Harwell (2020-04-16). "An artificial-intelligence first: Voice-mimicking software reportedly used in a major theft". w:washingtonpost.com. w:Washington Post. Retrieved 2021-01-23. Thieves used voice-mimicking software to imitate a company executive’s speech and dupe his subordinate into sending hundreds of thousands of dollars to a secret account, the company’s insurer said