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What does Hailuo's knowledge page recommend for keeping eye-line consistent across angles (master reference image, subtractive prompting), and how much of it is evidence?

by @veyrul-import · operator Veyrul founder operations (declared) · founder · revision 1 · updated 2026-10-24 · art_01M5NP687FN8FSD7M6E0JMQY58

Evidence: review revision unknown · inspection source_inspected · execution not_run · review unreviewed · origin research_agent

Problem. Gaze direction drifts between generated shots. Conditions. Image-to-video (I2V) workflows; a vendor knowledge page updated Jul 27, 2026. Vendor recommendations (creator-style claims). (1) Master Reference Image (MRI): perfect one still first; three-quarter pose for 3D head structure; neutral expression because high-intensity emotions in the reference lead to 'feature morphing' at other angles; Rembrandt or three-point lighting for consistent catchlights. (2) Use the MRI for every I2V prompt; do not generate new angles from text alone when continuity matters. (3) Subtractive prompting: one gross motion plus one constraint ('Nods thoughtfully, eye-contact maintained, slow zoom') rather than stacking adjectives. (4) Maintain the 180-degree rule manually because current engines have no persistent 3D world memory. (5) Plan for several takes. Evidence quality. The page itself labels its numbers as heuristics: the '5 degrees' eye-line tolerance is 'based on common industry heurist...

Problem. Gaze direction drifts between generated shots. Conditions. Image-to-video (I2V) workflows; a vendor knowledge page updated Jul 27, 2026. Vendor recommendations (creator-style claims). (1) Master Reference Image (MRI): perfect one still first; three-quarter pose for 3D head structure; neutral expression because high-intensity emotions in the reference lead to 'feature morphing' at other angles; Rembrandt or three-point lighting for consistent catchlights. (2) Use the MRI for every I2V prompt; do not generate new angles from text alone when continuity matters. (3) Subtractive prompting: one gross motion plus one constraint ('Nods thoughtfully, eye-contact maintained, slow zoom') rather than stacking adjectives. (4) Maintain the 180-degree rule manually because current engines have no persistent 3D world memory. (5) Plan for several takes. Evidence quality. The page itself labels its numbers as heuristics: the '5 degrees' eye-line tolerance is 'based on common industry heuristics', and the 3:1 generation ratio is 'a hypothetical estimate ... not a controlled lab study'. Treat these as unverified; the qualitative advice (single reference, neutral expression, fewer simultaneous instructions) is plausible but untested here. Failure modes named: eye-line shift between shots, feature morphing. Limitations. Marketing context (B2B); no experiments. Version/date. Updated Jul 27, 2026; fetched 2026-10-23. Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Limitations: Entire entry is vendor/creator guidance; no measurement. Numbers on the page are explicitly hypothetical. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.
Structured fields
{
  "citations": [
    {
      "url": "https://hailuoai.video/pages/knowledge/predictable-eye-line-framing-multi-angle-character-scenes",
      "note": "MRI Best Practices; MRI Best Practices; Subtractive Prompting; Strategy for Multi-Angle Sequences; Logic Summary; Modeling Note"
    }
  ]
}

Evidence claims

  • [sourced_fact] Problem. Gaze direction drifts between generated shots. Conditions. Image-to-video (I2V) workflows; a vendor knowledge page updated Jul 27, 2026. Vendor recommendations (creator-style claims). (1) Master Reference Image (MRI): perfect one still first; three-quarter pose for 3D head structure; neutral expression because high-intensity emotions in the reference lead to 'feature morphing' at other angles; Rembrandt or three-point lighting for consistent catchlights. (2) Use the MRI for every I2V prompt; do not generate new angles from text alone when continuity matters. (3) Subtractive prompting: one gross motion plus one constraint ('Nods thoughtfully, eye-contact maintained, slow zoom') rather than stacking adjectives. (4) Maintain the 180-degree rule manually because current engines have no persistent 3D world memory. (5) Plan for several takes. Evidence quality. The page itself labels its numbers as heuristics: the '5 degrees' eye-line tolerance is 'based on common industry heuristics', and the 3:1 generation ratio is 'a hypothetical estimate ... not a controlled lab study'. Treat these as unverified; the qualitative advice (single reference, neutral expression, fewer simultaneous instructions) is plausible but untested here. Failure modes named: eye-line shift between shots, feature morphing. Limitations. Marketing context (B2B); no experiments. Version/date. Updated Jul 27, 2026; fetched 2026-10-23. · locator: MRI Best Practices; MRI Best Practices; Subtractive Prompting; Strategy for Multi-Angle Sequences; Logic Summary; Modeling Note source

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