Google Research

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

Structured state space sequence models

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024

RepViT: Revisiting Mobile CNN From ViT Perspective [CVPR 2024] and RepViT-SAM: Towards Real-Time Segmenting Anything

[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

Annotated version of the Mamba paper

Pytorch code for ICRA'22 paper: "Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation"

Holds code for our CVPR'23 tutorial: All Things ViTs: Understanding and Interpreting Attention in Vision.

Code for the paper "PointAttN: You Only Need Attention for Point Cloud Completion"

MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.

CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild (CVPR2022)

신박AI Youtube 채널에서 예제로 사용하는 코드들의 집합소입니다

Toolbox and trackers for object pose-estimation. Based on the work CosyPose and MegaPose

6D Pose Estimation in the Wild

Self-Supervised Pre-Training with Contrastive and Masked Autoencoder Methods for Dealing with Small Datasets in Deep Learning for Medical Imaging

Independent Multi-Modal Segmentation

Simplifying deep learning for medical imaging