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Back to videodreamer23/videodreamer23.github.io

Open-source alternatives to Videodreamer23.github.io

30 open-source projects similar to videodreamer23/videodreamer23.github.io, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Videodreamer23.github.io alternative.

  • ailab-cvc/videocrafterailab-cvc avatar

    ailab-cvc/videocrafter

    5,063View on GitHub↗

    Videocrafter is a latent diffusion model designed for AI video synthesis. It functions as both a text-to-video and image-to-video generation system, synthesizing high-quality video sequences from descriptive text prompts or static image inputs. The model utilizes a diffusion-based neural network to transform inputs into animated content, ensuring visual consistency and temporal coherence throughout the generated sequences. This allows for the creation of custom video clips and the animation of static images into fluid motion.

    Python
    View on GitHub↗5,063
  • aim-uofa/gendefA

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  • ali-vilab/vaceali-vilab avatar

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    3,645View on GitHub↗

    VACE is a set of software tools and frameworks for reference-guided video generation, diffusion-based editing, and video-to-video translation. It provides utilities to produce new video content and modify existing sequences by using reference materials to guide visual style, subject matter, and composition. The framework enables video-to-video translation and synthesis, allowing for the update of visual styles and depth. It also functions as a video editor for modifying properties and content through reference-guided transformations. The system covers localized video editing and inpainting,

    Pythonvideo-editingvideo-generation
    View on GitHub↗3,645
  • alibaba/animate-anythingA

    alibaba/animate-anything

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  • alpha-vllm/lumina-t2xAlpha-VLLM avatar

    Alpha-VLLM/Lumina-T2X

    2,250View on GitHub↗

    Lumina-T2X is a unified framework for Text to Any Modality Generation

    Pythonaigcdiffusiondiffusion-model
    View on GitHub↗2,250

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  • alpha-vllm/lumina-videoA

    Alpha-VLLM/Lumina-Video

    0View on GitHub↗
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    aniki-ly/FlowZero

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    anonymous0769/DreamVideo

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  • anonymous0x233/reuseanddiffuseA

    anonymous0x233/ReuseAndDiffuse

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    araachie/yoda

    0View on GitHub↗
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  • arthur-qiu/longercrafterA

    arthur-qiu/LongerCrafter

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    baaivision/NOVA

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  • buggyyang/rvdbuggyyang avatar

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    Python
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  • chenhsing/simdaC

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    DA-Group-PKU/Magic-1-For-1

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    daeunni/VideoRepair

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  • damo-vilab/videocomposerD

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  • doubiiu/dynamicrafterDoubiiu avatar

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    3,001View on GitHub↗

    ECCV 2024, Oral DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

    Pythonimage-animationimage-to-videovideo-generation
    View on GitHub↗3,001
  • dreamoving/dreamoving-projectdreamoving avatar

    dreamoving/dreamoving-project

    1,792View on GitHub↗

    Official implementation of DreaMoving

    View on GitHub↗1,792
  • dvlab-research/jengaD

    dvlab-research/Jenga

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  • feizc/video-in-contextF

    feizc/Video-In-Context

    0View on GitHub↗
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  • g-u-n/gen-l-videoG

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  • gongyeliu/stylecrafterG

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  • guoyww/animatediffguoyww avatar

    guoyww/AnimateDiff

    12,144View on GitHub↗

    AnimateDiff is a latent diffusion video generator and text-to-video diffusion framework. It converts existing text-to-image diffusion models into animation generators by applying specialized motion modules, allowing for the creation of video sequences without modifying the original base model. The project provides an image-to-video animation framework that uses sparse RGB images, sketches, or structural keyframe constraints to guide generation. It further distinguishes itself with a motion adapter system that injects cinematic camera movements, such as zooming, panning, and tilting, into anim

    Python
    View on GitHub↗12,144
  • hong-yu-zhang/magiccompH

    Hong-yu-Zhang/MagicComp

    0View on GitHub↗
    View on GitHub↗0
  • hvision-nku/storydiffusionHVision-NKU avatar

    HVision-NKU/StoryDiffusion

    6,430View on GitHub↗

    StoryDiffusion is a generative AI system designed for consistent character image and video generation. It utilizes a pluggable cross-attention module to inject shared character representations into pretrained diffusion models, allowing for visual identity stability across multiple images and scenes without retraining the base model. The project features a video generation pipeline that produces temporally coherent sequences from text prompts or condition images. It employs a latent space motion interpolator to predict intermediate frames and semantic motion, enabling long-range video generati

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    View on GitHub↗6,430
  • ai-forever/kandinskyvideoA

    ai-forever/KandinskyVideo

    0View on GitHub↗
    View on GitHub↗0