ptrnn

llama

Inference code for LLaMA models

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Open-Assistant

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Grounded-Segment-Anything

Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

ImageBind

ImageBind One Embedding Space to Bind Them All

Awesome-Incremental-Learning

Awesome Incremental Learning

InternGPT

InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)

Awesome-Anything

General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX

LVM

S-LoRA

S-LoRA: Serving Thousands of Concurrent LoRA Adapters

CRATE

Code for CRATE (Coding RAte reduction TransformEr).

hiera

Hiera: A fast, powerful, and simple hierarchical vision transformer.

Segment-Any-Anomaly

Official implementation of "Segment Any Anomaly without Training via Hybrid Prompt Regularization (SAA+)".

Awesome-CV-Foundational-Models

Diffusion-Models-in-Vision-A-Survey

This repository categorizes the papers about diffusion models applied in computer vision according to their target task. The classifcation is based on our survey: https://arxiv.org/abs/2209.04747v1

prodigy

The Prodigy optimizer and its variants for training neural networks.

visual_token_matching

[ICLR'23 Oral] Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching

UniPose

Official implementation of the paper "UniPose : Detecting Any Keypoints"

GShell

Official implentation of "Ghost on the Shell: An Expressive Representation of General 3D Shapes" (ICLR 2024 Oral)

PoseNDF

Implementation of Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields

Plain-DETR

[ICCV2023] DETR Doesn’t Need Multi-Scale or Locality Design

Partial_Distance_Correlation

This is the official GitHub for paper: On the Versatile Uses of Partial Distance Correlation in Deep Learning, in ECCV 2022

SegPrompt

Official Implementation of ICCV 2023 Paper - SegPrompt: Boosting Open-World Segmentation via Category-level Prompt Learning

SLiMe

1-shot image segmentation using Stable Diffusion

torchdeq

Modern Fixed Point Systems using Pytorch

deep-latent-particles-pytorch

[ICML 2022] Official PyTorch implementation of the paper "Unsupervised Image Representation Learning with Deep Latent Particles"

CPP

This is the official implementation for Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models.

blad

Official Implementation of "Box-Level Active Detection (CVPR2023 highlight)"