nistarlwc

nistarlwc's Stars

• purse1996/opencv_example

  some examples of OpenCV

  Language:C++2923

• Keep-Passion/ImageStitch

  A Fast Algorithm for Material Image Sequential Stitching

  Language:Python18150

• OpenStitching/stitching

  A Python package for fast and robust Image Stitching

  Language:Python1.9k147

• LeapLabTHU/EfficientTrain

  1.5−3.0× lossless training or pre-training speedup. An off-the-shelf, easy-to-implement algorithm for the efficient training of foundation visual backbones.

  Language:Python1888

• CVHub520/X-AnyLabeling

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

  Language:Python3k342

• cnulab/RealNet

  Offical implementation of "RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection (CVPR 2024)"

  Language:Python1325

• sjtuplayer/anomalydiffusion

  [AAAI 2024] AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model

  Language:Jupyter Notebook10311

• apple/ml-destseg

  Language:Python607

• GrandpaXun242/AdaBLDM

  The implement for paper : "A Novel Approach to Industrial Defect Generation through Blended Latent Diffusion Model with Online Adaptation"

  Language:Python40

• TooTouch/MemSeg

  Unofficial re-implementation of MemSeg for Anomaly Detection

  Language:Jupyter Notebook17129

• 315386775/DeepLearing-Interview-Awesome-2024

  AIGC-interview/CV-interview/LLMs-interview面试问题与答案集合仓，同时包含工作和科研过程中的新想法、新问题、新资源与新项目

  1.1k114

• KyanChen/TTP

  Implement of the paper "Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection"

  Language:Python563

• MoonUsagi/AOI_Lab

  Visual Insepction (include Anomaly Detect & Text Detection & OCR & BarCode Read)

  11

• ByChelsea/CLIP-AD

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

  Language:Python162

• mala-lab/InCTRL

  Official implementation of CVPR'24 paper 'Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts'.

  Language:Python8112

• mkirchhof/url

  Uncertainty-aware representation learning (URL) benchmark

  Language:Python862

• caoyunkang/Segment-Any-Anomaly

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

  Language:Jupyter Notebook68172

• Scientific-Computing-Lab-NRCN/ChangeChip

  Language:Python247

• likyoo/open-cd

  A Change Detection Repo Standing on the Shoulders of Giants

  Language:Python42562

• caixiongjiang/FastSegFormer

  [Computers and Electronics in Agriculture 2024] FastSegFormer: A knowledge distillation-based method for real-time semantic segmentation of surface defects in navel oranges.

  Language:Python131

• Ldhlwh/DFMGAN

  [AAAI 2023] Official implementation of "Few-Shot Defect Image Generation via Defect-Aware Feature Manipulation".

  Language:Python718

• zhangzjn/OCR-GAN

  [TIP 2023] Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection

  Language:Python366

• CASIA-IVA-Lab/AnomalyGPT

  [AAAI 2024 Oral] AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models

  Language:Python66881

• 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)。

  1.2k118

• xzz777/SCTNet

  Official implementation of SCTNet (AAAI2024)

  Language:Python14510

• rximg/EfficientAD

  unofficial version of EfficientAD

  Language:Python10618

• 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 Notebook14.1k1.3k

• pytorch/TensorRT

  PyTorch/TorchScript/FX compiler for NVIDIA GPUs using TensorRT

  Language:Python2.4k333

• BBBBchan/Awesome-Semi-Supervised-Semantic-Segmentation

  A summary of recent semi-supervised semantic segmentation methods

  12514

• NVIDIA/CUDALibrarySamples

  CUDA Library Samples

  Language:Cuda1.4k291