Human motion as foreign language.
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Updated
Dec 6, 2023
Human motion as foreign language.
Basic models and their code in the field of image generation.
Vector Quantized Variational Auto-Encoder (VQ-VAE): Neural Discrete Representation Learning
This presentation, conducted for the "Natural Language Processing" course, delves into the paper's content, which addresses the challenge of generating images for a story using a text-to-image framework. The paper can be accessed at https://arxiv.org/abs/2210.08465.
Generative models nano version for fun. No STOA here, nano first.
생성모델을 이용한 ASMR 컨텐츠 제작 프로젝트
A hierarchical VQ-VAE implementation in Flax
Generating images in different contexts using GANs and Variational Autoencoders
Medical Image Latent Space Visualization Using VQ-VAE
Conditional Video/GIF Synthesis implementation using PyTorch Lightning and Hydra. This method utilizes Vector Quantization Variational AutoEncoder (VQ-VAE) with Discrete Denoising Diffusion Probabilistic Models (D3PM) to generate novel videos.
A generative machine learning model that generates noval foley sounds
VQ-VAE-based image tokenizer for model-based RL
Variational autoencoders implemented in Tensorflow.
Branch of the original Project "dome272/VQGAN-pytorch" adding an inference file for the VQGAN (Not for the VQGAN Transformers)
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