[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
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Updated
Nov 18, 2025 - Python
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
[CVPR 2023] | RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors
Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
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Pytorch implementation of Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
Streamlit Tutorial (ex: stock price dashboard, cartoon-stylegan, vqgan-clip, stylemixing, styleclip, sefa)
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
Zero-Shot Text-to-Image Generation VQGAN+CLIP Dockerized
Official Implement of Multi-Stage Multi-Codebook (MSMC) TTS
PyTorch codes for "Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors", ACM MM2022 (Oral)
[ICCV 2025] SimVQ: Addressing Representation Collapse in Vector Quantized Models with One Linear Layer
A research-friendly PyTorch Lightning toolkit for training, fine-tuning, and benchmarking AutoencoderKL for Stable Diffusion, FLUX, and beyond.
Colabs for text prompt steered image generators
VQ-VAE/GAN implementation in pytorch-lightning
NTIRE 2022 - Image Inpainting Challenge
Fast and controllable text-to-image model.
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab.
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