Showing 4 open source projects for "apache framework"

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    Wan2.2

    Wan2.2

    Wan2.2: Open and Advanced Large-Scale Video Generative Model

    Wan2.2 is a major upgrade to the Wan series of open and advanced large-scale video generative models, incorporating cutting-edge innovations to boost video generation quality and efficiency. It introduces a Mixture-of-Experts (MoE) architecture that splits the denoising process across specialized expert models, increasing total model capacity without raising computational costs. Wan2.2 integrates meticulously curated cinematic aesthetic data, enabling precise control over lighting,...
    Downloads: 105 This Week
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  • 2
    LTX-Video

    LTX-Video

    Official repository for LTX-Video

    LTX-Video is a sophisticated multimedia processing framework from Lightricks designed to handle high-quality video editing, compositing, and transformation tasks with performance and scalability. It provides runtime components that efficiently decode, encode, and manipulate video streams, frame buffers, and audio tracks while exposing a rich API for building customized editing features like transitions, effects, color grading, and keyframe automation. The toolkit is built with both real-time...
    Downloads: 11 This Week
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  • 3
    CogVideo

    CogVideo

    Text and image to video generation: CogVideoX and CogVideo

    CogVideo is an open-source family of advanced video generation models that can create videos from text, images, or existing video inputs. Built on large-scale Transformer and diffusion architectures, it enables multimodal generation across text-to-video, image-to-video, and video continuation tasks. The latest CogVideoX models offer higher resolution outputs, longer video durations, and improved controllability through prompt engineering. The project includes tools for inference,...
    Downloads: 6 This Week
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  • 4
    Wan Move

    Wan Move

    Motion-controllable Video Generation via Latent Trajectory Guidance

    Wan Move is an open-source research codebase for motion-controllable video generation that focuses on enabling fine-grained control of motion within generative video models. It is designed to guide the temporal evolution of visual content by leveraging latent trajectory guidance, allowing users to manipulate how objects move over time without modifying the underlying generative architecture. By representing motion information as dense point trajectories and integrating them into the latent...
    Downloads: 0 This Week
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