Ace-blue

Ace-blue's Stars

• lm-sys/FastChat

  An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.

  Language:Python38.2k3541.9k4.7k

• Loyalsoldier/clash-rules

  🦄️ 🎃 👻 Clash Premium 规则集(RULE-SET)，兼容 ClashX Pro、Clash for Windows 等基于 Clash Premium 内核的客户端。

  20.5k1012951.8k

• facebookresearch/segment-anything-2

  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 the model.

  Language:Jupyter Notebook11.1k64259944

• ShiArthur03/ShiArthur03

  Language:MATLAB10.3k321.4k1.9k

• IDEA-Research/GroundingDINO

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

  Language:Python7.7k46329776

• andandroidor/ourtv

  稳定、蓝光、高清、电视直播

  4.9k390310

• lyuwenyu/RT-DETR

  [CVPR 2024] Official RT-DETR (RTDETR paddle pytorch), Real-Time DEtection TRansformer, DETRs Beat YOLOs on Real-time Object Detection. 🔥 🔥 🔥

  Language:Python3.4k28512398

• dvlab-research/LISA

  Project Page for "LISA: Reasoning Segmentation via Large Language Model"

  Language:Python2.1k12173144

• M-3LAB/awesome-industrial-anomaly-detection

  Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。

  2k7516180

• keyu-tian/SparK

  [ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"

  Language:Python1.3k208980

• lxtGH/OMG-Seg

  OMG-LLaVA and OMG-Seg codebase [CVPR-24 and NeurIPS-24]

  Language:Python1.3k196246

• linux-do/override

  啥也不是

  Language:Go1.1k831256

• caoyunkang/Segment-Any-Anomaly

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

  Language:Jupyter Notebook778103878

• ZjjConan/SimAM

  The official pytorch implemention of our ICML-2021 paper "SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks".

  Language:Python43452436

• xrli-U/MuSc

  This is an official PyTorch implementation for "MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images" (MuSc ICLR2024).

  Language:Python37144026

• zqhang/AnomalyCLIP

  Official implementation for AnomalyCLIP (ICLR 2024)

  Language:Python35896643

• cqylunlun/GLASS

  [ECCV 2024] Official Implementation and Dataset Release for "A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization"

  Language:Python25195637

• boson-ai/RPBench-Auto

  An automated pipeline for evaluating LLMs for role-playing.

  Language:Python162449

• wangjunchi/LLMSeg

  LLM-Seg: Bridging Image Segmentation and Large Language Model Reasoning

  Language:Python14041016

• FuNz-0/PromptAD

  Official implementation of CVPR 2024 PromptAD: Learning Prompts with Only Normal Samples for Few-Shot Anomaly Detection

  Language:Python1344308

• OPPOMKLab/u-LLaVA

  u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model

  Language:Python130256

• Hao840/OFAKD

  PyTorch code and checkpoints release for OFA-KD: https://arxiv.org/abs/2310.19444

  Language:Python11323819

• gyguo/PixelDistillation

  Official code for TPAMI2024 paper: Pixel Distillation: Cost-flexible Distillation across Image Sizes and Heterogeneous Networks

  Language:Python56131

• ZjjConan/Multi-Modal-Adapter

  The official pytorch implemention of our CVPR-2024 paper "MMA: Multi-Modal Adapter for Vision-Language Models".

  Language:Python44432

• CityU-AIM-Group/SOMA

  [ICCV' 23 ORAL] Novel Scenes & Classes: Towards Adaptive Open-set Object Detection

  Language:Python412104

• Hlings/AsyFOD

  (CVPR2023) The PyTorch implementation of the "AsyFOD: An Asymmetric Adaptation Paradigm for Few-Shot Domain Adaptive Object Detection".

  Language:Python393193

• ByChelsea/CLIP-AD

  CLIP-AD is an upgraded version of the zero-shot anomaly detection method we proposed for the VAND challenge.

  Language:Python32222

• AIS-Clemson/VisionGPT

  LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation

  Language:Python28302

• zhangyin1996/ISP-Teacher

  [AAAI 2024] ISP-Teacher: Image Signal Process with Disentanglement Regularization for Unsupervised Domain Adaptive Dark Object Detection

  Language:Python18260

• BJT-bjt/MAGA

  The code of the paper "Multi-view contrastive clustering via integrating graph aggregation and confidence enhancement"

  Language:Python4100