4 projects for "modules" with 2 filters applied:

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  • 1
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    ...The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation across base and target domains to measure how well the model retains its general knowledge while specializing as needed. It includes utilities to fine-tune vision-language embeddings, compute prompt or adapter updates, and benchmark across transfer and retention metrics. MetaCLIP is especially suited for real-world settings where a model must continuously incorporate new visual categories or domains over time.
    Downloads: 0 This Week
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  • 2
    Vision Transformer Pytorch

    Vision Transformer Pytorch

    Implementation of Vision Transformer, a simple way to achieve SOTA

    This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and...
    Downloads: 0 This Week
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  • 3
    General C++ Library, with modules for Computer Vision, Pattern Recognition and much more.
    Downloads: 1 This Week
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  • 4
    BADGr

    BADGr

    Toolbox for Box Approximation, Decomposition, and Grasping

    ...The toolbox was developed in the Computer Vision & Active Perception Lab, at the Royal Institute of Technology, as a participant of the EU research project PACO-PLUS, and published at the project's end in Summer 2010. BADGr provides modules to approximate the shape of a point cloud (possibly from sensor data) by box primitives. These box primitives then serve as a base for the generation of box-based pre-grasp hypotheses for robot grippers.
    Downloads: 0 This Week
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