Quantised Global Autoencoder: A Holistic Approach to Representing Visual Data

16 July 2024

Papers citing "Quantised Global Autoencoder: A Holistic Approach to Representing Visual Data"

8 / 8 papers shown

Title
An Image is Worth 32 Tokens for Reconstruction and Generation Qihang Yu Mark Weber XueQing Deng Xiaohui Shen Daniel Cremers Liang-Chieh Chen VLM ViT 139 94 0 11 Jun 2024
Discrete Acoustic Space for an Efficient Sampling in Neural Text-To-Speech Mu Li Jonas Rohnke Antonio Bonafonte Mateusz Lajszczak Trevor Wood DRL 61 2 0 24 Oct 2021
Vector-quantized Image Modeling with Improved VQGAN Jiahui Yu Xin Li Jing Yu Koh Han Zhang Ruoming Pang James Qin Alexander Ku Yuanzhong Xu Jason Baldridge Yonghui Wu ViT VLM DRL 109 514 0 09 Oct 2021
VideoGPT: Video Generation using VQ-VAE and Transformers Wilson Yan Yunzhi Zhang Pieter Abbeel A. Srinivas ViT VGen 295 498 0 20 Apr 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 391 4,941 0 24 Feb 2021
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 226 5,008 0 02 Nov 2017
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.8K 77,133 0 18 May 2015
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 546 27,295 0 01 Sep 2014