ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2112.01799
  4. Cited By
Global Context with Discrete Diffusion in Vector Quantised Modelling for
  Image Generation

Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation

3 December 2021
Minghui Hu
Yujie Wang
Tat-Jen Cham
Jianfei Yang
P.N.Suganthan
    DiffM
ArXivPDFHTML

Papers citing "Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation"

41 / 41 papers shown
Title
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Harshit Varma
Dheeraj M. Nagaraj
Karthikeyan Shanmugam
VLM
139
3
0
27 May 2024
ImageBART: Bidirectional Context with Multinomial Diffusion for
  Autoregressive Image Synthesis
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis
Patrick Esser
Robin Rombach
A. Blattmann
Bjorn Ommer
DiffM
89
160
0
19 Aug 2021
Structured Denoising Diffusion Models in Discrete State-Spaces
Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin
Daniel D. Johnson
Jonathan Ho
Daniel Tarlow
Rianne van den Berg
DiffM
167
941
0
07 Jul 2021
Variational Diffusion Models
Variational Diffusion Models
Diederik P. Kingma
Tim Salimans
Ben Poole
Jonathan Ho
DiffM
178
1,121
0
01 Jul 2021
Diffusion Priors In Variational Autoencoders
Diffusion Priors In Variational Autoencoders
Antoine Wehenkel
Gilles Louppe
DiffM
46
23
0
29 Jun 2021
Score-based Generative Modeling in Latent Space
Score-based Generative Modeling in Latent Space
Arash Vahdat
Karsten Kreis
Jan Kautz
DiffM
65
682
0
10 Jun 2021
Cascaded Diffusion Models for High Fidelity Image Generation
Cascaded Diffusion Models for High Fidelity Image Generation
Jonathan Ho
Chitwan Saharia
William Chan
David J. Fleet
Mohammad Norouzi
Tim Salimans
161
1,222
0
30 May 2021
Diffusion Models Beat GANs on Image Synthesis
Diffusion Models Beat GANs on Image Synthesis
Prafulla Dhariwal
Alex Nichol
224
7,857
0
11 May 2021
Zero-Shot Text-to-Image Generation
Zero-Shot Text-to-Image Generation
Aditya A. Ramesh
Mikhail Pavlov
Gabriel Goh
Scott Gray
Chelsea Voss
Alec Radford
Mark Chen
Ilya Sutskever
VLM
397
4,953
0
24 Feb 2021
Improved Denoising Diffusion Probabilistic Models
Improved Denoising Diffusion Probabilistic Models
Alex Nichol
Prafulla Dhariwal
DiffM
337
3,686
0
18 Feb 2021
Transformers in Vision: A Survey
Transformers in Vision: A Survey
Salman Khan
Muzammal Naseer
Munawar Hayat
Syed Waqas Zamir
Fahad Shahbaz Khan
M. Shah
ViT
302
2,516
0
04 Jan 2021
Taming Transformers for High-Resolution Image Synthesis
Taming Transformers for High-Resolution Image Synthesis
Patrick Esser
Robin Rombach
Bjorn Ommer
ViT
126
2,962
0
17 Dec 2020
Dual Contradistinctive Generative Autoencoder
Dual Contradistinctive Generative Autoencoder
Gaurav Parmar
Dacheng Li
Kwonjoon Lee
Zhuowen Tu
GAN
46
82
0
19 Nov 2020
Denoising Diffusion Implicit Models
Denoising Diffusion Implicit Models
Jiaming Song
Chenlin Meng
Stefano Ermon
VLM
DiffM
278
7,384
0
06 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based
  Models
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao
Karsten Kreis
Jan Kautz
Arash Vahdat
61
124
0
01 Oct 2020
DiffWave: A Versatile Diffusion Model for Audio Synthesis
DiffWave: A Versatile Diffusion Model for Audio Synthesis
Zhifeng Kong
Ming-Yu Liu
Jiaji Huang
Kexin Zhao
Bryan Catanzaro
DiffM
BDL
155
1,457
0
21 Sep 2020
NVAE: A Deep Hierarchical Variational Autoencoder
NVAE: A Deep Hierarchical Variational Autoencoder
Arash Vahdat
Jan Kautz
BDL
69
910
0
08 Jul 2020
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
628
18,096
0
19 Jun 2020
Generative Modeling by Estimating Gradients of the Data Distribution
Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song
Stefano Ermon
SyDa
DiffM
258
3,916
0
12 Jul 2019
Generating Diverse High-Fidelity Images with VQ-VAE-2
Generating Diverse High-Fidelity Images with VQ-VAE-2
Ali Razavi
Aaron van den Oord
Oriol Vinyals
DRL
BDL
147
1,815
0
02 Jun 2019
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
583
10,561
0
12 Dec 2018
Glow: Generative Flow with Invertible 1x1 Convolutions
Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma
Prafulla Dhariwal
BDL
DRL
295
3,134
0
09 Jul 2018
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin
Matthias Huser
Francesco Locatello
Heiko Strathmann
Gunnar Rätsch
BDL
AI4TS
52
139
0
06 Jun 2018
Theory and Experiments on Vector Quantized Autoencoders
Theory and Experiments on Vector Quantized Autoencoders
Aurko Roy
Ashish Vaswani
Arvind Neelakantan
Niki Parmar
69
88
0
28 May 2018
Group Normalization
Group Normalization
Yuxin Wu
Kaiming He
231
3,660
0
22 Mar 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
Eli Shechtman
Oliver Wang
EGVM
377
11,795
0
11 Jan 2018
PixelSNAIL: An Improved Autoregressive Generative Model
PixelSNAIL: An Improved Autoregressive Generative Model
Xi Chen
Nikhil Mishra
Mostafa Rohaninejad
Pieter Abbeel
DRL
DiffM
BDL
GAN
74
275
0
28 Dec 2017
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDL
SSL
OCL
226
5,019
0
02 Nov 2017
Progressive Growing of GANs for Improved Quality, Stability, and
  Variation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras
Timo Aila
S. Laine
J. Lehtinen
GAN
134
7,361
0
27 Oct 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
701
131,652
0
12 Jun 2017
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial
  Networks
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Jun-Yan Zhu
Taesung Park
Phillip Isola
Alexei A. Efros
GAN
125
5,553
0
30 Mar 2017
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture
  Likelihood and Other Modifications
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Tim Salimans
A. Karpathy
Xi Chen
Diederik P. Kingma
105
942
0
19 Jan 2017
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
334
5,364
0
03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random
  Variables
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison
A. Mnih
Yee Whye Teh
BDL
193
2,533
0
02 Nov 2016
Conditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN Decoders
Aaron van den Oord
Nal Kalchbrenner
Oriol Vinyals
L. Espeholt
Alex Graves
Koray Kavukcuoglu
VLM
204
2,513
0
16 Jun 2016
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
477
2,570
0
25 Jan 2016
LSUN: Construction of a Large-scale Image Dataset using Deep Learning
  with Humans in the Loop
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Feng Yu
Ari Seff
Yinda Zhang
Shuran Song
Thomas Funkhouser
Jianxiong Xiao
91
2,338
0
10 Jun 2015
Scheduled Sampling for Sequence Prediction with Recurrent Neural
  Networks
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Samy Bengio
Oriol Vinyals
Navdeep Jaitly
Noam M. Shazeer
145
2,034
0
09 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
1.8K
77,196
0
18 May 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Narain Sohl-Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
SyDa
DiffM
301
6,949
0
12 Mar 2015
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
452
16,929
0
20 Dec 2013
1