Search Results - Vector quantized autoencoder*

Hierarchical Vector-Quantized Variational Autoencoder and Vector Credibility Mechanism for High-Quality Image Inpainting by Li, Cheng, Xu, Dan, Chen, Kuai

“… To restore textures at a fine-grained level, we propose an image inpainting method based on a hierarchical VQ-VAE with a vector credibility mechanism…”
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Quaternion Vector Quantized Variational Autoencoder by Luo, Hui, Liu, Xin, Sun, Jian, Zhang, Yang

“…Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in generative tasks…”
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Vector-Quantized Variational AutoEncoder for pansharpening by Talbi, Farid, Chikr Elmezouar, Miloud, Boutellaa, Elhocine, Alim, Fatiha

“… This paper describes a new, efficient, and accurate pansharpening architecture. The Vector-Quantized Variational AutoEncoder (VQ-VAE…”
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Variable Rate Allocation for Vector-Quantized Autoencoders by Baldassarre, Federico, El-Nouby, Alaaeldin, Jegou, Herve

“…Vector-quantized autoencoders have recently gained interest in image compression, generation and self-supervised learning…”
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A vector quantized masked autoencoder for audiovisual speech emotion recognition by Sadok, Samir, Leglaive, Simon, Séguier, Renaud

“… The model includes vector quantized variational autoencoders that compress raw audio and visual speech data into discrete tokens…”
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FactorVQVAE: Discrete latent factor model via Vector Quantized Variational Autoencoder by Kim, Namhyoung, Ock, Seung Eun, Song, Jae Wook

“…This study introduces FactorVQVAE, the first integration of the Vector Quantized Variational Autoencoder (VQVAE…”
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Attention-based vector quantized variational autoencoder for anomaly detection by using orthogonal subspace constraints by Yu, Qien, Dai, Shengxin, Dong, Ran, Ikuno, Soichiro

“…This paper introduces a new framework that uses a vector quantized variational autoencoder (VQVAE…”
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Frequency enhanced vector quantized variational autoencoder for structural vibration response compression by Xue, Zhilin, An, Yonghui, Ou, Jinping

“…•The frequency enhanced vector quantized variational autoencoder (FEVQVAE) is proposed for structural vibration response compression…”
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Predicting anatomical variations in radiotherapy with a vector quantized variational autoencoder generative model by Zou, Yue, Li, Zhenhao, Zhang, Menghan, Li, Ziwei, Yin, Xiaojie, Yang, Long, Hu, Weigang, Wang, Jiazhou

“… Predicting these changes may benefit adaptive radiotherapy (ART) in nasopharyngeal cancer. Purpose This study proposes a vector quantized variational autoencoder (VQ‐VAE…”
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Data augmentation for Gram-stain images based on Vector Quantized Variational AutoEncoder by V, Shwetha, Prasad, Keerthana, Mukhopadhyay, Chiranjay, Banerjee, Barnini

“… In this regard, we investigate a novel application of the Variational AutoEncoder. Specifically, the Vector Quantized Variational AutoEncoder model is trained to generate the Gram-stain images…”
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Enhancing into the Codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders by Casebeer, Jonah, Vale, Vinjai, Isik, Umut, Valin, Jean-Marc, Giri, Ritwik, Krishnaswamy, Arvindh

“…Audio codecs based on discretized neural autoencoders have recently been developed and shown to provide significantly higher compression levels for comparable quality speech out-put…”
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Avoiding Domain Drift and Constant Predictions with Diffusion Enhanced Vector-Quantized Autoencoders for Temperature Predictions by Lampl, Nina, de Freitas, Joao Machado, Fuchs, Alexander, Brezina, Benedikt, Klitzsch, Michael, Pernkopf, Franz

“… Using a vector-quantized autoencoder can mitigate the problem as it can map predictions back to the source domain, but it leads to almost constant predictions…”
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S-HR-VQVAE: Sequential Hierarchical Residual Learning Vector Quantized Variational Autoencoder for Video Prediction by Adiban, Mohammad, Stefanov, Kalin, Siniscalchi, Sabato Marco, Salvi, Giampiero

“… (i) a novel hierarchical residual learning vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel autoregressive spatiotemporal predictive model…”
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SSL-VQ: vector-quantized variational autoencoders for semi-supervised prediction of therapeutic targets across diverse diseases by Namba, Satoko, Li, Chen, Yuyama Otani, Noriko, Yamanishi, Yoshihiro

“… rare diseases, intractable diseases). Results This study presents a novel machine learning approach using multimodal vector-quantized variational autoencoders (VQ-VAEs…”
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466.4-Gbit/s PCS-64QAM wireless transmission enhanced by dual-polarized SISO link and vector-quantized variational autoencoders by Liu, Xiang, Zhang, Jiao, Zhu, Min, Xin, Zhigang, Dong Tong, Wei, Wang, Yunwu, Cai, Yuancheng, Hua, Bingchang, Lei, Mingzheng, Liu, Bo, Yu, Jianjun

“…) wireless delivery at 92.5 GHz. This is achieved by employing a likelihood-aware vector-quantized variational autoencoder (VQ-VAE…”
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A Vector Quantized Variational Autoencoder (VQ-VAE) Autoregressive Neural F0 Model for Statistical Parametric Speech Synthesis by Wang, Xin, Takaki, Shinji, Yamagishi, Junichi, King, Simon, Tokuda, Keiichi

“… In subjective evaluations, a deep AR model (DAR) outperformed an RNN. Here, we propose a Vector Quantized Variational Autoencoder (VQ-VAE…”
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SVQ-VAE: Federated-Learning-Based Semantic-Aware Communication for Vehicular Networks by Jin, Zhu, Li, Yundi, Song, Tiecheng, Jia, Wen-Kang, Song, Xiaoqin

“…The integration of semantic communication technology into intelligent vehicular networks represents a promising research direction, as it significantly reduces…”
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Leveraging Vector-Quantized Variational Autoencoder Inner Metrics for Anomaly Detection by Gangloff, Hugo, Pham, Minh-Tan, Courtrai, Luc, Lefevre, Sebastien

“… In this context, deep generative models are widely used, in particular Variational Autoencoder (VAE) models. VAEs have been extended to Vector-Quantized VAEs…”
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Vector Quantized Variational Autoencoder-Based Compressive Sampling Method for Time Series in Structural Health Monitoring by Liang, Ge, Ji, Zhenglin, Zhong, Qunhong, Huang, Yong, Han, Kun

“…The theory of compressive sampling (CS) has revolutionized data compression technology by capitalizing on the inherent sparsity of a signal to enable signal…”
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Anomaly Detection Through Latent Space Restoration Using Vector Quantized Variational Autoencoders by Marimont, Sergio Naval, Tarroni, Giacomo

“…We propose an out-of-distribution detection method that combines density and restoration-based approaches using Vector-Quantized Variational Auto-Encoders (VQ-VAEs…”
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