Showing 5 open source projects for "visual code"

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  • 1
    Exclusively Dark Image Dataset

    Exclusively Dark Image Dataset

    ExDARK dataset is the largest collection of low-light images

    ...It has been widely used in studies of low-light image enhancement, deep learning approaches, and domain adaptation for vision models. Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition.
    Downloads: 2 This Week
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  • 2
    Exposure Correction

    Exposure Correction

    Learning multi-scale deep model correcting over- and under- exposed

    ...This allows the model to preserve fine details while correcting global lighting inconsistencies. The repository includes pre-trained models, datasets, and training/testing code to enable reproducibility and experimentation. By leveraging this framework, researchers and developers can apply exposure correction to a wide range of natural images, improving visual quality without manual editing. The project serves both as a research reference and a practical tool for computational photography and image enhancement.
    Downloads: 0 This Week
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  • 3

    PsyExTool

    psychophysical experiment control, data collection and visualization

    ...At the end of the session, the data can be stored or exported for further analysis. The structure of the program may incorporate and combine additional methods for data collection and stimuli presentation. The code is under MIT license. Comments and questions are welcome.
    Downloads: 0 This Week
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  • 4
    CFNet

    CFNet

    Training a Correlation Filter end-to-end allows lightweight networks

    ...Henriques, Andrea Vedaldi, and Philip H. S. Torr. The framework combines correlation filters with deep convolutional neural networks to create an efficient and accurate visual object tracker. Unlike traditional correlation filter trackers that rely on hand-crafted features, CFNet learns feature representations directly from data in an end-to-end fashion. This allows the tracker to be both computationally efficient and robust to appearance changes such as scale, rotation, and illumination variations. The repository provides pre-trained models, training code, and testing scripts for evaluating the tracker on standard benchmarks. ...
    Downloads: 1 This Week
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  • 5
    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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