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A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/
From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
A WebUI for Efficient Fine-Tuning of 100+ LLMs (ACL 2024)
Pytorch implementation of "An intriguing failing of convolutional neural networks and the CoordConv solution" - https://arxiv.org/abs/1807.03247
⭐️ Companies that don't have a broken hiring process
Open source implementation of "Vision Transformers Need Registers"
Segment Anything Model for Medical Image Segmentation: paper list and open-source project summary
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
[ICML 2024] Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Images
The repository contains a simple pipeline for training Nuclei Segmentation Datasets of Histopathology Images.
Segment Anything in Medical Images
repository for 360 panorama image generation based on Stable Diffusion
Use Grounding DINO, Segment Anything, and GPT-4V to label images with segmentation masks for use in training smaller, fine-tuned models.
Official Pytorch implementation of Dual Cross-Attention for Medical Image Segmentation
A Probabilistic U-Net for segmentation of ambiguous images implemented in PyTorch
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
[ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"
Segment Anything for Microscopy
Focal Loss of multi-classification in tensorflow
A collection of loss functions for medical image segmentation
Effective Data Augmentation With Diffusion Models