{"adoption": {"forks": 303, "observed_at": "2026-08-28T04:07:25.007698+00:00", "stars": 2846}, "canonical_url": "https://ross.abutalabs.com/products/musev", "card": {"archived": false, "artifact_type": "library", "description": "MuseV: Infinite-length and High Fidelity Virtual Human Video Generation with Visual Conditioned Parallel Denoising", "domain": ["artificial-intelligence", "deep-learning", "image-processing", "computer-vision"], "enriched": true, "function": ["video-processing", "image-processing", "machine-learning", "deep-learning", "stable-diffusion"], "health_score": 20, "homepage": null, "language": "Python", "license": "NOASSERTION", "license_family": "other", "maturity": "active", "member_repos": ["TMElyralab/MuseV"], "name": "TMElyralab/MuseV", "platform": ["python"], "pushed_at": "2024-06-28T04:21:48+00:00", "repo": "TMElyralab/MuseV", "stars": 2846, "tags": ["diffusion-models", "image-to-video", "text-to-video", "video-generation", "virtual-human", "parallel-denoising", "infinite-length", "generative-ai", "video", "linux", "gpu", "docker"], "topics": ["diffusion", "human-video-generation", "image2video", "video-generation", "infinite-length", "musev"], "urls": [], "use_cases": ["generate videos of virtual humans from a single reference image", "create infinite-length talking avatar videos", "convert text prompts into human video clips", "restyle existing videos with reference images (video2video)", "build virtual human pipelines with MuseTalk and MusePose", "run a gradio demo to generate videos in a browser"], "what_it_is": "MuseV is a diffusion-based framework for generating high-fidelity virtual human videos of infinite length using a Visual Conditioned Parallel Denoising scheme. It supports Image2Video, Text2Image2Video, and Video2Video generation and is compatible with the Stable Diffusion ecosystem including LoRA, ControlNet, and IP-Adapter.", "when_to_avoid": ["you need real-time lip sync alone - use MuseTalk instead", "you need pose-controlled animation - use MusePose instead", "you lack a GPU or cannot run large diffusion models locally", "you need a production-ready, fully documented training pipeline - training code was not yet released"], "when_to_choose": ["you need diffusion-based image-to-video generation of human characters", "you want long or infinite-length video generation beyond typical clip limits", "you want compatibility with Stable Diffusion checkpoints, LoRA, and ControlNet", "you are building a virtual human / digital avatar generation stack"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/musev", "repo": "TMElyralab/MuseV", "role": "main", "score": 25}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:07:25.007698+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T07:37:01.668279+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "f6ff7126f0b62dc3eebe95fe950a6e1c979a92c093b6d98521c46eda722cdd56", "fetched_at": "2026-08-28T04:07:25.007698+00:00", "kind": "readme", "missing": false, "url": "https://github.com/TMElyralab/MuseV"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 63, "rhythm": 35}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_releases", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 891, "days_push": 796, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 25, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}