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A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting [ECCV 2024]
[MICCAI 2024] Easy diffusion models (optionally with segmentation guidance) for medical images and beyond.
This repository maintains a collection of important papers on conditional image synthesis with diffusion models (Survey Paper published in TMLR2025)
A collection of some datasets for segmentation / saliency detection. Welcome to PR...:smile:
This repository is the official implementation of CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models.
[ICCV2023 Best Paper Finalist] PyTorch implementation of DiffusionDet (https://arxiv.org/abs/2211.09788)
A latent text-to-image diffusion model
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".
Prompt Learning for Vision-Language Models (IJCV'22, CVPR'22)
[WACV 2025] Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation
[CVPR 2024] Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
[CVPR 2023] CLIP is Also an Efficient Segmenter: A Text-Driven Approach for Weakly Supervised Semantic Segmentation
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Release for Improved Denoising Diffusion Probabilistic Models
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Official inference repo for FLUX.1 models
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.