{"schema":"record/v1","id":"art_01M5NBFVZS8GQ1E8KE8BREJDHY","type":"article","revision":1,"etag":"\"r1.s0\"","title":"How can you puppeteer AI video with physical props or rough animation (Time-to-Move), and how reliable is it?","summary":"Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated. Mickmumpitz (2025-12-17): Time-to-Move (TTM, Apache-2.0 repo) is training-free and works with diffusion video models (he uses Wan 2.2; paper also names CogVideoX and SVD). Make a control video by moving toys/cutouts on a stick or by rough After Effects/Blender animation; TTM's \"dual-clock denoising\" uses lower noise where the character moves (follow the motion) and higher noise elsewhere (clean background). His ComfyUI prep: SAM 3 masks the character (add negative clicks on the stick), Qwen Image Edit removes the stick in start/end frames (also fix hovering by masking larger and prompting \"stand on the table... do not change the look\"), then TTM with start+end frames fo...","status":"active","body":{"text":"Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated.\n\nMickmumpitz (2025-12-17): Time-to-Move (TTM, Apache-2.0 repo) is training-free and works with diffusion video models (he uses Wan 2.2; paper also names CogVideoX and SVD). Make a control video by moving toys/cutouts on a stick or by rough After Effects/Blender animation; TTM's \"dual-clock denoising\" uses lower noise where the character moves (follow the motion) and higher noise elsewhere (clean background). His ComfyUI prep: SAM 3 masks the character (add negative clicks on the stick), Qwen Image Edit removes the stick in start/end frames (also fix hovering by masking larger and prompting \"stand on the table... do not change the look\"), then TTM with start+end frames for identity stability; preview after ~3 steps and change seed/prompt if bad. Reported reliability: about 70% of shots worked first try, versus \"countless iterations\" with Wan VACE previously. For himself as a 15-year-old he used Wan Animate (driving performance + reference), which was inconsistent across shots until he trained a character LoRA (AI Toolkit) on family photos; Wan 2.2 LoRAs transfer to Wan Animate.\n\nCurator qualifications: Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated. Video metadata checked; documentation excerpts (if any) located; creator statements not curator-verified.\n\nLimitations: Creator statements were read by discovery from auto-captions (ASR) in a browser panel; not re-verified by the curator. 70% is self-reported for his own shot set; LoRA of a real person (himself as minor, with parental photos) raises consent/likeness considerations for others.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://www.youtube.com/watch?v=pUb58eAZ3pc","note":"0:00-2:00; 2:00; 6:02; 8:02; GitHub API"},{"url":"https://github.com/time-to-move/TTM","note":"0:00-2:00; 2:00; 6:02; 8:02; GitHub API"}]},"categories":["T06","T07","T08"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"metadata_checked","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://www.youtube.com/watch?v=pUb58eAZ3pc","claim":"Mickmumpitz (2025-12-17): Time-to-Move (TTM, Apache-2.0 repo) is training-free and works with diffusion video models (he uses Wan 2.2; paper also names CogVideoX and SVD). Make a control video by moving toys/cutouts on a stick or by rough After Effects/Blender animation; TTM's \"dual-clock denoising\" uses lower noise where the character moves (follow the motion) and higher noise elsewhere (clean background). His ComfyUI prep: SAM 3 masks the character (add negative clicks on the stick), Qwen Image Edit removes the stick in start/end frames (also fix hovering by masking larger and prompting \"stand on the table... do not change the look\"), then TTM with start+end frames for identity stability; preview after ~3 steps and change seed/prompt if bad. Reported reliability: about 70% of shots worked first try, versus \"countless iterations\" with Wan VACE previously. For himself as a 15-year-old he used Wan Animate (driving performance + reference), which was inconsistent across shots until he trained a character LoRA (AI Toolkit) on family photos; Wan 2.2 LoRAs transfer to Wan Animate.","locator":"0:00-2:00; 2:00; 6:02; 8:02; GitHub API","classification":"sourced_fact"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-1859928ed08c44dfbae801cdfd25c608e5a35b54/record.json#p-1859928ed08c44dfbae801cdfd25c608e5a35b54/record","import_batch_id":"pipe-32dbca32937eb4ba94c7ab392617786389ba984f","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-32dbca32937eb4ba94c7ab392617786389ba984f","original":{"body":{"text":"Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated.\n\nMickmumpitz (2025-12-17): Time-to-Move (TTM, Apache-2.0 repo) is training-free and works with diffusion video models (he uses Wan 2.2; paper also names CogVideoX and SVD). Make a control video by moving toys/cutouts on a stick or by rough After Effects/Blender animation; TTM's \"dual-clock denoising\" uses lower noise where the character moves (follow the motion) and higher noise elsewhere (clean background). His ComfyUI prep: SAM 3 masks the character (add negative clicks on the stick), Qwen Image Edit removes the stick in start/end frames (also fix hovering by masking larger and prompting \"stand on the table... do not change the look\"), then TTM with start+end frames for identity stability; preview after ~3 steps and change seed/prompt if bad. Reported reliability: about 70% of shots worked first try, versus \"countless iterations\" with Wan VACE previously. For himself as a 15-year-old he used Wan Animate (driving performance + reference), which was inconsistent across shots until he trained a character LoRA (AI Toolkit) on family photos; Wan 2.2 LoRAs transfer to Wan Animate.\n\nCurator qualifications: Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated. Video metadata checked; documentation excerpts (if any) located; creator statements not curator-verified.\n\nLimitations: Creator statements were read by discovery from auto-captions (ASR) in a browser panel; not re-verified by the curator. 70% is self-reported for his own shot set; LoRA of a real person (himself as minor, with parental photos) raises consent/likeness considerations for others.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://www.youtube.com/watch?v=pUb58eAZ3pc","note":"0:00-2:00; 2:00; 6:02; 8:02; GitHub API"},{"url":"https://github.com/time-to-move/TTM","note":"0:00-2:00; 2:00; 6:02; 8:02; GitHub API"}]},"tags":[],"type":"article","links":[],"title":"How can you puppeteer AI video with physical props or rough animation (Time-to-Move), and how reliable is it?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"Creator-reported: statements attributed to the creator(s) come from discovery's reading of auto-caption transcript excerpts; the curator checked the video metadata (title, date, length) and any cited documentation pages, not the spoken claims. Nothing was tested; promotional or sponsored framing applies where stated. Mickmumpitz (2025-12-17): Time-to-Move (TTM, Apache-2.0 repo) is training-free and works with diffusion video models (he uses Wan 2.2; paper also names CogVideoX and SVD). Make a control video by moving toys/cutouts on a stick or by rough After Effects/Blender animation; TTM's \"dual-clock denoising\" uses lower noise where the character moves (follow the motion) and higher noise elsewhere (clean background). His ComfyUI prep: SAM 3 masks the character (add negative clicks on the stick), Qwen Image Edit removes the stick in start/end frames (also fix hovering by masking larger and prompting \"stand on the table... do not change the look\"), then TTM with start+end frames fo...","evidence":{"claims":[{"url":"https://www.youtube.com/watch?v=pUb58eAZ3pc","claim":"Mickmumpitz (2025-12-17): Time-to-Move (TTM, Apache-2.0 repo) is training-free and works with diffusion video models (he uses Wan 2.2; paper also names CogVideoX and SVD). Make a control video by moving toys/cutouts on a stick or by rough After Effects/Blender animation; TTM's \"dual-clock denoising\" uses lower noise where the character moves (follow the motion) and higher noise elsewhere (clean background). His ComfyUI prep: SAM 3 masks the character (add negative clicks on the stick), Qwen Image Edit removes the stick in start/end frames (also fix hovering by masking larger and prompting \"stand on the table... do not change the look\"), then TTM with start+end frames for identity stability; preview after ~3 steps and change seed/prompt if bad. Reported reliability: about 70% of shots worked first try, versus \"countless iterations\" with Wan VACE previously. For himself as a 15-year-old he used Wan Animate (driving performance + reference), which was inconsistent across shots until he trained a character LoRA (AI Toolkit) on family photos; Wan 2.2 LoRAs transfer to Wan Animate.","locator":"0:00-2:00; 2:00; 6:02; 8:02; GitHub API","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"metadata_checked","execution_record_ids":[]},"language":"en","categories":["T06","T07","T08"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":1,"topic_ids":[],"confidence":"70% is self-reported for his own shot set; LoRA of a real person (himself as minor, with parental photos) raises consent/likeness considerations for others.","limitations":["Creator statements were read by discovery from auto-captions (ASR) in a browser panel; not re-verified by the curator.","70% is self-reported for his own shot set; LoRA of a real person (himself as minor, with parental photos) raises consent/likeness considerations for others.","Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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