Showing 3 open source projects for "benchmark"

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    BasicSR

    BasicSR

    Winning Solution in NTIRE19 Challenges on Video Restoration

    BasicSR is a deep learning framework designed for advanced video restoration tasks such as video super-resolution, deblurring, and denoising. Unlike single-image restoration models, EDVR addresses the temporal dimension by aligning multiple video frames using deformable convolutional layers in a coarse-to-fine manner, allowing it to effectively handle large motion and complex scene dynamics. The architecture includes bespoke modules (e.g., Pyramid, Cascading and Deformable alignment and...
    Downloads: 0 This Week
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    YouTube-8M

    YouTube-8M

    Starter code for working with the YouTube-8M dataset

    ...The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured at ICCV 2019), enabling researchers and practitioners to benchmark video classification models on large-scale datasets with over millions of labeled videos. The code demonstrates how to process frame-level features, train logistic and deep learning models, evaluate them using metrics like global Average Precision (gAP) and mean Average Precision (mAP), and export trained models for MediaPipe inference.
    Downloads: 0 This Week
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  • 3
    Video Nonlocal Net

    Video Nonlocal Net

    Non-local Neural Networks for Video Classification

    ...Efficient implementations keep memory and compute manageable so the blocks can be added without rewriting the entire backbone. The result is a practical, drop-in mechanism for upgrading purely local video models into context-aware networks with strong benchmark performance.
    Downloads: 0 This Week
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