[D] Which open source models can replicate wonder dynamics's drag'n'drop cg characters?

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning

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  • segment-anything

    The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  • Use Segmentation Model (SAM) combined with Inpainting model (E2FGVI) and Xmem to cut out the live action subject.

  • E2FGVI

    Official code for "Towards An End-to-End Framework for Flow-Guided Video Inpainting" (CVPR2022)

  • Use Segmentation Model (SAM) combined with Inpainting model (E2FGVI) and Xmem to cut out the live action subject.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • XMem

    [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model

  • Use Segmentation Model (SAM) combined with Inpainting model (E2FGVI) and Xmem to cut out the live action subject.

  • Track-Anything

    Track-Anything is a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything, XMem, and E2FGVI.

  • The Track-Anything tool already implements this

  • openpose

    OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

  • Perhaps something like OpenPose for pose estimation?

  • lama

    🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

  • You may be able to remove the actor with lama. https://github.com/advimman/lama

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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