Showing 7 open source projects for "waifu2x-caffe"

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  • 1
    MTCNN Face Detection Alignment

    MTCNN Face Detection Alignment

    Joint Face Detection and Alignment

    ...The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. Non-maximum suppression and bounding box regression at each stage. Online hard sample mining to improve training robustness.
    Downloads: 0 This Week
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  • 2
    VGGFace2

    VGGFace2

    VGGFace2 Dataset for Face Recognition

    VGGFace2 is a large-scale face recognition dataset developed to support research on facial recognition across variations in pose, age, illumination, and identity. It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities,...
    Downloads: 23 This Week
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  • 3
    SFD

    SFD

    S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017

    ...Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. It includes training scripts, evaluation code, and pre-trained models that achieve strong results on popular benchmarks such as AFW, PASCAL Face, FDDB, and WIDER FACE. The framework is optimized for speed and accuracy, making it suitable for both academic research and practical applications in computer vision.
    Downloads: 2 This Week
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  • 4
    Faster R-CNN

    Faster R-CNN

    Object detection framework based on deep convolutional networks

    This repository provides a MATLAB / Caffe re-implementation of the Faster R-CNN object detection framework (originally from Ren et al. 2015). The Faster R-CNN architecture combines a Region Proposal Network (RPN) with a Fast R-CNN style detection network to share convolutional feature maps and thus speed up detection. The repo includes code to train, test, and deploy Faster R-CNN models under the MATLAB / Caffe environment, example configuration files, and model checkpoints. ...
    Downloads: 0 This Week
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  • 5
    Face Verification Experiment

    Face Verification Experiment

    Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch

    face_verification_experiment is a research repository focused on experiments in face verification using deep learning. It provides implementations and scripts for testing different neural network architectures and training strategies on face recognition and verification tasks. The project is designed to help researchers and practitioners evaluate the performance of models on standard datasets and explore techniques for improving accuracy. By offering experimental setups, it enables...
    Downloads: 2 This Week
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  • 6
    CRFasRNN

    CRFasRNN

    Semantic image segmentation method described in the ICCV 2015 paper

    ...This software allows you to test our algorithm on your own images – have a try and see if you can fool it, if you get some good examples you can send them to us. CRF-RNN has been developed as a custom Caffe layer named MultiStageMeanfieldLayer. Usage of this layer in the model definition prototxt file looks the following. Check the matlab-scripts or the python-scripts folder for more detailed examples.
    Downloads: 0 This Week
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  • 7
    Rcnn

    Rcnn

    R-CNN: Regions with Convolutional Neural Network Features

    This repository contains the original MATLAB implementation of R-CNN (Regions with Convolutional Neural Networks), a pioneering deep learning-based object detection framework. Developed by Ross Girshick, R-CNN combines region proposals with convolutional neural networks to detect objects in images. It was one of the first approaches to significantly improve performance on object detection benchmarks like PASCAL VOC.
    Downloads: 0 This Week
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