HLuLuu

HLuLuu's Stars

• CVHub520/X-AnyLabeling

  Effortless data labeling with AI support from Segment Anything and other awesome models.

  Language:Python4.1k470

• cvat-ai/cvat

  Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

  Language:Python12.6k3k

• UX-Decoder/Segment-Everything-Everywhere-All-At-Once

  [NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"

  Language:Python4.4k400

• UX-Decoder/Semantic-SAM

  [ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"

  Language:Python2.4k113

• ylsung/Ladder-Side-Tuning

  PyTorch codes for "LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning"

  Language:Python23010

• SysCV/sam-hq

  Segment Anything in High Quality [NeurIPS 2023]

  Language:Python3.7k224

• facebookresearch/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.

  Language:Jupyter Notebook47.6k5.6k

• huggingface/peft

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

  Language:Python16.4k1.6k

• ZhangYuanhan-AI/NOAH

  [TPAMI] Searching prompt modules for parameter-efficient transfer learning.

  Language:Python22211

• JieShibo/PETL-ViT

  [ICCV 2023 & AAAI 2023] Binary Adapters & FacT, [Tech report] Convpass

  Language:Python1718

• CASIA-IVA-Lab/FastSAM

  Fast Segment Anything

  Language:Python7.5k709

• z1069614715/objectdetection_script

  一些关于目标检测的脚本的改进思路代码，详细请看readme.md

  Language:Python5.4k478

• facebookresearch/dino

  PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

  Language:Python6.4k909

• facebookresearch/dinov2

  PyTorch code and models for the DINOv2 self-supervised learning method.

  Language:Jupyter Notebook9.2k819

• XoriieInpottn/docset

  A dataset format/utilities used to store document objects based on BSON.

  Language:Python4

• byungjae89/SPADE-pytorch

  PyTorch implementation of "Sub-Image Anomaly Detection with Deep Pyramid Correspondences"

  Language:Python23843

• IDEA-Research/Grounded-Segment-Anything

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

  Language:Jupyter Notebook15.1k1.4k

• IDEA-Research/GroundingDINO

  [ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

  Language:Python6.7k683

• devnag/pytorch-generative-adversarial-networks

  A very simple generative adversarial network (GAN) in PyTorch

  Language:Python1.5k449

• dice2o/BingGPT

  Desktop application of new Bing's AI-powered chat (Windows, macOS and Linux)

  Language:JavaScript9.3k709

• acheong08/EdgeGPT

  Reverse engineered API of Microsoft's Bing Chat AI

  Language:Python8.1k909

• YingYang/MEEG_connectivity

  Language:Python93

• taotu/VBLDS_Connectivity_EEG_fMRI

  Language:MATLAB11

• deepcharles/ruptures

  ruptures: change point detection in Python

  Language:Python1.6k163

• koshian2/inception-vae

  Variational Auto Encoder using Inception module in PyTorch

  Language:Python203

• yuanxiaosc/DeepImage-an-Image-to-Image-technology

  DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。

  Language:Python5.2k2k

• ChenJinBIT/HPDA

  Language:Python7

• lucidrains/denoising-diffusion-pytorch

  Implementation of Denoising Diffusion Probabilistic Model in Pytorch

  Language:Python8.3k1k

• diff-usion/Awesome-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML11.1k948

• facebookresearch/Detectron

  FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

  Language:Python26.3k5.5k