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Hierarchical Residu...
Hierarchical Residual Learning Based Vector Quantized Variational Autoencorder for Image Reconstruction and Generation
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- Adiban, Mohammad (författare)
- Norwegian University of Science and Technology Trondheim, Norway; Monash University Melbourne, Australia
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- Siniscalchi, Marco (författare)
- Norwegian University of Science and Technology Trondheim, Norway
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- Stefanov, Kalin (författare)
- Monash University Melbourne, Australia
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- Salvi, Giampiero (författare)
- KTH,Tal-kommunikation,Norwegian University of Science and Technology Trondheim, Norway,Tal, musik och hörsel, TMH
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(creator_code:org_t)
- British Machine Vision Association (BMVA), 2022
- 2022
- Engelska.
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Ingår i: The 33<sup>rd</sup> British Machine Vision Conference Proceedings. - : British Machine Vision Association (BMVA).
- Relaterad länk:
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https://bmvc2022.org...
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https://kth.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- We propose a multi-layer variational autoencoder method, we call HR-VQVAE, thatlearns hierarchical discrete representations of the data. By utilizing a novel objectivefunction, each layer in HR-VQVAE learns a discrete representation of the residual fromprevious layers through a vector quantized encoder. Furthermore, the representations ateach layer are hierarchically linked to those at previous layers. We evaluate our methodon the tasks of image reconstruction and generation. Experimental results demonstratethat the discrete representations learned by HR-VQVAE enable the decoder to reconstructhigh-quality images with less distortion than the baseline methods, namely VQVAE andVQVAE-2. HR-VQVAE can also generate high-quality and diverse images that outperform state-of-the-art generative models, providing further verification of the efficiency ofthe learned representations. The hierarchical nature of HR-VQVAE i) reduces the decoding search time, making the method particularly suitable for high-load tasks and ii) allowsto increase the codebook size without incurring the codebook collapse problem.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- Datalogi
- Computer Science
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)