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Synthetic human-like fakes: Difference between revisions
+ 2018 | science | Progressive Growing of GANs for Improved Quality, Stability, and Variation at arxiv.org (.pdf), colloquially known as ProGANs were presented by Nvidia researchers at the 2018 ICLR.
Juho Kunsola (talk | contribs) (+ CVPR 2021 at cvpr2021.thecvf.com) |
Juho Kunsola (talk | contribs) (+ 2018 | science | Progressive Growing of GANs for Improved Quality, Stability, and Variation at arxiv.org (.pdf), colloquially known as ProGANs were presented by Nvidia researchers at the 2018 ICLR.) |
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* '''2019''' | US state law | {{#lst:Current and possible laws and their application|Texas2019}} | * '''2019''' | US state law | {{#lst:Current and possible laws and their application|Texas2019}} | ||
* '''2019''' | US state law | {{#lst:Current and possible laws and their application|Virginia2019}} | * '''2019''' | US state law | {{#lst:Current and possible laws and their application|Virginia2019}} | ||
* 2019 | Science | [https://arxiv.org/pdf/1809.10460.pdf '''''Sample Efficient Adaptive Text-to-Speech''''' .pdf at arxiv.org], a 2019 paper from Google researchers, published as a conference paper at [[w:International Conference on Learning Representations]] (ICLR)<ref group="1st seen in" name="ConnectedPapers suggestion on Google Transfer learning 2018"> https://www.connectedpapers.com/main/8fc09dfcff78ac9057ff0834a83d23eb38ca198a/Transfer-Learning-from-Speaker-Verification-to-Multispeaker-TextToSpeech-Synthesis/graph</ref> | * '''2019''' | Science | [https://arxiv.org/pdf/1809.10460.pdf '''''Sample Efficient Adaptive Text-to-Speech''''' .pdf at arxiv.org], a 2019 paper from Google researchers, published as a conference paper at [[w:International Conference on Learning Representations]] (ICLR)<ref group="1st seen in" name="ConnectedPapers suggestion on Google Transfer learning 2018"> https://www.connectedpapers.com/main/8fc09dfcff78ac9057ff0834a83d23eb38ca198a/Transfer-Learning-from-Speaker-Verification-to-Multispeaker-TextToSpeech-Synthesis/graph</ref> | ||
* '''2019''' | science and demonstration | [https://arxiv.org/pdf/1905.09773.pdf ''''Speech2Face: Learning the Face Behind a Voice'''' at arXiv.org] a system for generating likely facial features based on the voice of a person, presented by the [[w:MIT Computer Science and Artificial Intelligence Laboratory]] at the 2019 [[w:Conference on Computer Vision and Pattern Recognition|w:CVPR]]. [https://github.com/saiteja-talluri/Speech2Face Speech2Face at github.com] This may develop to something that really causes problems. [https://neurohive.io/en/news/speech2face-neural-network-predicts-the-face-behind-a-voice/ "Speech2Face: Neural Network Predicts the Face Behind a Voice" reporing at neurohive.io], [https://belitsoft.com/speech-recognition-software-development/speech2face "Speech2Face Sees Voices and Hears Faces: Dreams Come True with AI" reporting at belitsoft.com] | * '''2019''' | science and demonstration | [https://arxiv.org/pdf/1905.09773.pdf ''''Speech2Face: Learning the Face Behind a Voice'''' at arXiv.org] a system for generating likely facial features based on the voice of a person, presented by the [[w:MIT Computer Science and Artificial Intelligence Laboratory]] at the 2019 [[w:Conference on Computer Vision and Pattern Recognition|w:CVPR]]. [https://github.com/saiteja-talluri/Speech2Face Speech2Face at github.com] This may develop to something that really causes problems. [https://neurohive.io/en/news/speech2face-neural-network-predicts-the-face-behind-a-voice/ "Speech2Face: Neural Network Predicts the Face Behind a Voice" reporing at neurohive.io], [https://belitsoft.com/speech-recognition-software-development/speech2face "Speech2Face Sees Voices and Hears Faces: Dreams Come True with AI" reporting at belitsoft.com] | ||
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* '''<font color="red">2018</font>''' | <font color="red">science</font> and <font color="red">demonstration</font> | The work [http://papers.nips.cc/paper/7700-transfer-learning-from-speaker-verification-to-multispeaker-text-to-speech-synthesis ''''Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis''''] ([https://arxiv.org/abs/1806.04558 at arXiv.org]) was presented at the 2018 [[w:Conference on Neural Information Processing Systems]] ('''NeurIPS'''). The pre-trained model is able to steal voices from a sample of only '''5 seconds''' with almost convincing results. | * '''<font color="red">2018</font>''' | <font color="red">science</font> and <font color="red">demonstration</font> | The work [http://papers.nips.cc/paper/7700-transfer-learning-from-speaker-verification-to-multispeaker-text-to-speech-synthesis ''''Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis''''] ([https://arxiv.org/abs/1806.04558 at arXiv.org]) was presented at the 2018 [[w:Conference on Neural Information Processing Systems]] ('''NeurIPS'''). The pre-trained model is able to steal voices from a sample of only '''5 seconds''' with almost convincing results. | ||
* '''2018''' | science | [https://arxiv.org/abs/1710.10196 '''Progressive Growing of GANs for Improved Quality, Stability, and Variation''' at arxiv.org] ([https://arxiv.org/pdf/1710.10196.pdf .pdf]), colloquially known as ProGANs were presented by Nvidia researchers at the [https://iclr.cc/Conferences/2018 2018 ICLR]. [[w:International Conference on Learning Representations]] | |||
* '''2018''' | demonstration | At the 2018 [[w:World Internet Conference]] in [[w:Wuzhen]] the [[w:Xinhua News Agency]] presented two digital look-alikes made to the resemblance of its real news anchors Qiu Hao ([[w:Chinese language]])<ref name="TheGuardian2018"> | * '''2018''' | demonstration | At the 2018 [[w:World Internet Conference]] in [[w:Wuzhen]] the [[w:Xinhua News Agency]] presented two digital look-alikes made to the resemblance of its real news anchors Qiu Hao ([[w:Chinese language]])<ref name="TheGuardian2018"> | ||