Implementation of Denoising Diffusion Probabilistic Model in Pytorch
AI-assisted RAW photo developer: GPT vision advisor proposes an EditRecipe, a deterministic Rust engine renders it — Lightroom-compatible XMP sidecars, 24 RAW formats + baked images, measured (not guessed) Lightroom mask geometry, local GUI/web UI, AI denoise & segmentation sidecars
Enhance Images with Javascript and AI. Increase resolution, retouch, denoise, and more. Open Source, Browser & Node Compatible, MIT License.
NVIDIA Real-time Denoising (NRD) library
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning
Autoregressive video generation with decoupled context-writing and denoising parameters, enabling up to 24-hour generation from 5s training windows.
Teaching-oriented PyTorch course for 3-D seismic denoising with DnCNN, SEG-Y I/O, GUI, notebook, and slides.
NVIDIA RTX Video Super Resolution for ComfyUI, optimized for long videos with disk-backed processing and low RAM usage. Supports AI upscaling, denoising, deblurring, H.264/HEVC NVENC encoding, audio preservation, and an integrated video preview.
CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising