Showing 15 open source projects for "matlab code generator"

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  • 1
    Image Fusion

    Image Fusion

    Deep Learning-based Image Fusion: A Survey

    This repository is a survey / code collection centered on deep learning–based image fusion (e.g. fusing infrared + visible light images, multi-modal fusion) methods. It catalogs many fusion algorithms (e.g. DenseFuse, FusionGAN, NestFuse, etc.), links to code implementations, and describes evaluation metrics. The repository includes a “General Evaluation Metric” subfolder containing objective fusion metrics. It is not a single monolithic tool, but rather a curated reference and aggregation...
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  • 2
    Segment Anything

    Segment Anything

    Provides code for running inference with the SegmentAnything Model

    Segment Anything (SAM) is a foundation model for image segmentation that’s designed to work “out of the box” on a wide variety of images without task-specific fine-tuning. It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A...
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  • 3
    Armadillo

    Armadillo

    fast C++ library for linear algebra & scientific computing

    * Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code
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    Downloads: 4,060 This Week
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  • 4
    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.
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  • 5
    DnCNN

    DnCNN

    Beyond a Gaussian Denoiser: Residual Learning of Deep CNN

    ...This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image super-resolution or JPEG deblocking in some variants. The repository includes training code (using MatConvNet / MATLAB), demo scripts, pretrained models, and evaluation routines. Single model handling multiple noise levels.
    Downloads: 3 This Week
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  • 6
    VRN

    VRN

    Code for "Large Pose 3D Face Reconstruction

    The VRN (Volumetric Regression Network) repository implements the “Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression” method. Instead of explicitly fitting a 3D model via landmark estimation and deformation, VRN treats the reconstruction task as volumetric segmentation: it learns a CNN to regress a 3D volume aligned to the input image, and then extracts a mesh via isosurface from that volume. The network is unguided (no 2D landmarks as intermediate)....
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  • 7
    CAM

    CAM

    Class Activation Mapping

    This repository implements Class Activation Mapping (CAM), a technique to expose the implicit attention of convolutional neural networks by generating heatmaps that highlight the most discriminative image regions influencing a network’s class prediction. The method involves modifying a CNN model slightly (e.g., using global average pooling before the final layer) to produce a weighted combination of feature maps as the class activation map. Integration with existing CNNs (with light...
    Downloads: 1 This Week
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  • 8
    Tiny

    Tiny

    Tiny Face Detector, CVPR 2017

    ...The code depends on MatConvNet, which must be compiled (with GPU / CUDA / cuDNN support) for full performance. Pretrained model provided (ResNet101-based, plus alternatives). Demo and evaluation scripts for benchmark datasets. Use of “foveal descriptors” to incorporate context for low-resolution faces. Pretrained model provided (ResNet101-based, plus alternatives).
    Downloads: 0 This Week
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  • 9

    OpenFace

    A state-of-the-art facial behavior analysis toolkit

    OpenFace is an advanced facial behavior analysis toolkit intended for computer vision and machine learning researchers, those in the affective computing community, and those who are simply interested in creating interactive applications based on facial behavior analysis. The OpenFace toolkit is capable of performing several complex facial analysis tasks, including facial landmark detection, eye-gaze estimation, head pose estimation and facial action unit recognition. OpenFace is able to...
    Downloads: 17 This Week
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  • 10
    ConvNet Burden

    ConvNet Burden

    Memory consumption and FLOP count estimates for convnets

    convnet-burden is a MATLAB toolbox / script collection estimating computational cost (FLOPs) and memory consumption of various convolutional neural network architectures. It lets users compute approximate burdens (in FLOPs, memory) for standard image classification CNN models (e.g. ResNet, VGG) based on network definitions. The tool helps researchers compare the computational efficiency of architectures or quantify resource needs. Estimation of memory consumption (e.g. feature map sizes,...
    Downloads: 0 This Week
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  • 11
    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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  • 12
    OpenCE

    OpenCE

    Contrast Enhancement Techniques for low-light images

    OpenCE is an open source implementation of the paper Cascaded Pyramid Network for Multi-Person Pose Estimation (CVPR 2018) by Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, and Jian Sun. The framework provides a complete training and evaluation pipeline for human pose estimation using a cascaded pyramid network (CPN). OpenCE leverages a feature pyramid structure combined with a refinement stage to improve keypoint detection accuracy across multiple scales, particularly for...
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  • 13
    ECO

    ECO

    Matlab implementation of the ECO tracker

    ECO (Efficient Convolution Operators for Tracking) is a high-performance object tracking algorithm developed by Martin Danelljan and collaborators. It is based on discriminative correlation filters and designed to handle appearance changes, occlusions, and scale variations in visual object tracking tasks. The code provides a MATLAB implementation of the ECO and ECO-HC (high-speed) variants and was one of the top performers on multiple visual tracking benchmarks.
    Downloads: 0 This Week
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  • 14
    HashingBaselineForImageRetrieval

    HashingBaselineForImageRetrieval

    Various hashing methods for image retrieval and serves as the baseline

    This repository provides baseline implementations of deep supervised hashing methods for image retrieval tasks using PyTorch. It includes clean, minimal code for several hashing algorithms designed to map images into compact binary codes while preserving similarity in feature space, enabling fast and scalable retrieval from large image datasets.
    Downloads: 0 This Week
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  • 15
    Netvlad

    Netvlad

    NetVLAD: CNN architecture for weakly supervised place recognition

    NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets.
    Downloads: 0 This Week
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