GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
- pytorch
- gan
- deep-learning
- super-resolution
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GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
High-Resolution Image Synthesis with Latent Diffusion Models
A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
We propose Prism, a dynamic sparse attention framework for natively training joint video-audio generation models at 2K.
Official Hi3D v1.0: high-resolution 3D geometry refinement built on Sparc3D. Inference code, model weights, and documentation.
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
[ECCV 2026] Official implementation of "HRDiT: Training-Free High-Resolution Image Generation with Off-the-Shelf Diffusion Transformer Models"
MatAnyone-E: Sparse Memory Propagation for Efficient High-Resolution Video Matting
Official implementation of "AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers"
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs. The first merge library where every operation is mathematically guaranteed to converge.