1145 lines
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scene-actor-extraction
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Optimizer Experiments (prior round)
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Findings
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Model Bake-off & Re-tune (full log)
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Optimizer Experiments (prior round)
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Service Conversion (proposal)
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|
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|
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<li class="md-nav__item">
|
||
<a href="../best-model/" class="md-nav__link">
|
||
|
||
|
||
|
||
<span class="md-ellipsis">
|
||
|
||
|
||
Best Model
|
||
|
||
|
||
|
||
</span>
|
||
|
||
|
||
|
||
</a>
|
||
</li>
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
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|
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<a href="../gallery-scope/" class="md-nav__link">
|
||
|
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|
||
|
||
<span class="md-ellipsis">
|
||
|
||
|
||
Gallery Scope (Full vs. Limited)
|
||
|
||
|
||
|
||
</span>
|
||
|
||
|
||
|
||
</a>
|
||
</li>
|
||
|
||
|
||
|
||
|
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|
||
|
||
|
||
|
||
|
||
|
||
<li class="md-nav__item">
|
||
<a href="../pose-expansion/" class="md-nav__link">
|
||
|
||
|
||
|
||
<span class="md-ellipsis">
|
||
|
||
|
||
Pose Expansion
|
||
|
||
|
||
|
||
</span>
|
||
|
||
|
||
|
||
</a>
|
||
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|
||
|
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|
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|
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|
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|
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|
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|
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<li class="md-nav__item">
|
||
<a href="../lvface-deep-dive/" class="md-nav__link">
|
||
|
||
|
||
|
||
<span class="md-ellipsis">
|
||
|
||
|
||
LVFace Deep Dive
|
||
|
||
|
||
|
||
</span>
|
||
|
||
|
||
|
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</a>
|
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|
||
|
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|
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|
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|
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|
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</nav>
|
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|
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<li class="md-nav__item">
|
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<a href="../model-bakeoff/" class="md-nav__link">
|
||
|
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|
||
|
||
<span class="md-ellipsis">
|
||
|
||
|
||
Model Bake-off & Re-tune (full log)
|
||
|
||
|
||
|
||
</span>
|
||
|
||
|
||
|
||
</a>
|
||
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|
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|
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|
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|
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|
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|
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<input class="md-nav__toggle md-toggle" type="checkbox" id="__toc">
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<label class="md-nav__link md-nav__link--active" for="__toc">
|
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|
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|
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|
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<span class="md-ellipsis">
|
||
|
||
|
||
Optimizer Experiments (prior round)
|
||
|
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|
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|
||
</span>
|
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|
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|
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|
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<span class="md-nav__icon md-icon"></span>
|
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</label>
|
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|
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<a href="./" class="md-nav__link md-nav__link--active">
|
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|
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|
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|
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<span class="md-ellipsis">
|
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|
||
|
||
Optimizer Experiments (prior round)
|
||
|
||
|
||
|
||
</span>
|
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|
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|
||
|
||
</a>
|
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|
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|
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|
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<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
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<span class="md-nav__icon md-icon"></span>
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Table of contents
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<li class="md-nav__item">
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<span class="md-ellipsis">
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TL;DR — what changed
|
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</span>
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</a>
|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#ground-truth" class="md-nav__link">
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<span class="md-ellipsis">
|
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|
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Ground truth
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</span>
|
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#the-scoring-metric-evolved-through-review" class="md-nav__link">
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<span class="md-ellipsis">
|
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|
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The scoring metric (evolved through review)
|
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|
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</span>
|
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#the-gallery-coverage-gap" class="md-nav__link">
|
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<span class="md-ellipsis">
|
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|
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The gallery coverage gap
|
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|
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</span>
|
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#optimizer" class="md-nav__link">
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<span class="md-ellipsis">
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Optimizer
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|
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</span>
|
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#replay-architecture-how-the-sweep-is-cheap" class="md-nav__link">
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<span class="md-ellipsis">
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|
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Replay architecture (how the sweep is cheap)
|
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</span>
|
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</a>
|
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|
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</li>
|
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<li class="md-nav__item">
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<a href="#reproduce" class="md-nav__link">
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<span class="md-ellipsis">
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Reproduce
|
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|
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</a>
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</li>
|
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|
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</ul>
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</nav>
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</li>
|
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|
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<a href="../service-conversion/" class="md-nav__link">
|
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<span class="md-ellipsis">
|
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|
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|
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Service Conversion (proposal)
|
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|
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|
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|
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</span>
|
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|
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|
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|
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</a>
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|
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|
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|
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</ul>
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</nav>
|
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</div>
|
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</div>
|
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</div>
|
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|
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|
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|
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<div class="md-sidebar md-sidebar--secondary" data-md-component="sidebar" data-md-type="toc" >
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<div class="md-sidebar__scrollwrap">
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<div class="md-sidebar__inner">
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<nav class="md-nav md-nav--secondary" aria-label="Table of contents">
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<label class="md-nav__title" for="__toc">
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<span class="md-nav__icon md-icon"></span>
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Table of contents
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<ul class="md-nav__list" data-md-component="toc" data-md-scrollfix>
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<li class="md-nav__item">
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<a href="#tldr-what-changed" class="md-nav__link">
|
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<span class="md-ellipsis">
|
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|
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TL;DR — what changed
|
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</span>
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</a>
|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#ground-truth" class="md-nav__link">
|
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<span class="md-ellipsis">
|
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|
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Ground truth
|
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|
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</span>
|
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#the-scoring-metric-evolved-through-review" class="md-nav__link">
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<span class="md-ellipsis">
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The scoring metric (evolved through review)
|
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</span>
|
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#the-gallery-coverage-gap" class="md-nav__link">
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<span class="md-ellipsis">
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The gallery coverage gap
|
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</span>
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</a>
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</li>
|
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<li class="md-nav__item">
|
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<a href="#optimizer" class="md-nav__link">
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Optimizer
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</a>
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</li>
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<li class="md-nav__item">
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<a href="#replay-architecture-how-the-sweep-is-cheap" class="md-nav__link">
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<span class="md-ellipsis">
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|
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Replay architecture (how the sweep is cheap)
|
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|
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</span>
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</a>
|
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|
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</li>
|
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|
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<li class="md-nav__item">
|
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<a href="#reproduce" class="md-nav__link">
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<span class="md-ellipsis">
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Reproduce
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</span>
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</a>
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</li>
|
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|
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</ul>
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</nav>
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</div>
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</div>
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</div>
|
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<div class="md-content" data-md-component="content">
|
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|
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<article class="md-content__inner md-typeset">
|
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|
||
|
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|
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|
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|
||
<h1 id="threshold-optimization-against-amazon-x-ray-experiment-log">Threshold optimization against Amazon X-Ray — experiment log<a class="headerlink" href="#threshold-optimization-against-amazon-x-ray-experiment-log" title="Permanent link">¶</a></h1>
|
||
<p>Record of the July 2026 work that tuned the pipeline's recognition/tracking defaults
|
||
against ground-truth per-scene actor presence, and the tooling built to do it.</p>
|
||
<h2 id="tldr-what-changed">TL;DR — what changed<a class="headerlink" href="#tldr-what-changed" title="Permanent link">¶</a></h2>
|
||
<table>
|
||
<thead>
|
||
<tr>
|
||
<th>knob</th>
|
||
<th>old default</th>
|
||
<th>new default</th>
|
||
<th>why</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<td><code>prob_threshold</code></td>
|
||
<td>0.99</td>
|
||
<td><strong>0.76</strong></td>
|
||
<td>0.99 was far too strict — halved recall for a fraction of a precision point. DE optimum, tightly converged.</td>
|
||
</tr>
|
||
<tr>
|
||
<td><code>extinction_sec</code></td>
|
||
<td>5.0</td>
|
||
<td><strong>1.5</strong></td>
|
||
<td>Long extinction smears presence into later scenes → FPs. DE converged tightly low.</td>
|
||
</tr>
|
||
<tr>
|
||
<td><code>anneal_sec</code></td>
|
||
<td>10.0</td>
|
||
<td>10.0 (unchanged)</td>
|
||
<td>DE found it <strong>insensitive</strong> (F1 flat ±0.3pp across 3–26s) — kept the round default.</td>
|
||
</tr>
|
||
<tr>
|
||
<td><code>detector_conf</code></td>
|
||
<td>0.5</td>
|
||
<td>0.5 (unchanged)</td>
|
||
<td>Sweep showed raising it only trades recall for precision at a net F1 loss — near-threshold detections are real faces, not phantoms.</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
<p>Net effect on the 9-film benchmark (strict per-scene, augmented gallery):
|
||
recall <strong>58% → ~72%</strong>, F1 <strong>70% → ~76%</strong>, precision ~85%, at no meaningful precision cost.</p>
|
||
<h2 id="ground-truth">Ground truth<a class="headerlink" href="#ground-truth" title="Permanent link">¶</a></h2>
|
||
<p>Public scene-level <strong>Amazon X-Ray</strong> dataset (Zenodo DOI 10.5281/zenodo.17659734,
|
||
CC-BY-4.0): per movie, <code>people.csv</code> (name_id/person/character), <code>scenes.csv</code>
|
||
(scene/start/end ms), <code>people_in_scenes.csv</code>. Films matched to the library by an
|
||
<strong>authoritative Jellyfin ID join</strong> (query <code>/Items?IncludeItemTypes=Movie&Fields=
|
||
ProviderIds,Path</code>, join Imdb/Tmdb against X-Ray metadata) — NOT fuzzy title matching,
|
||
which collides badly (TV episodes vs same-named films). 9 genuine films with source
|
||
video on disk: Benny & Joon, Café Society, Downton Abbey: A New Era, Lord of War,
|
||
Lovelace, The Many Saints of Newark, Scarface, Sound of Metal, Valerian.</p>
|
||
<h2 id="the-scoring-metric-evolved-through-review">The scoring metric (evolved through review)<a class="headerlink" href="#the-scoring-metric-evolved-through-review" title="Permanent link">¶</a></h2>
|
||
<p>Comparison unit is the <strong>X-Ray scene</strong>, not sampled timepoints. For each scene
|
||
<code>[start,end]</code>: predicted set = <strong>union</strong> of actors detected anywhere in the span;
|
||
GT set = actors X-Ray lists for that scene. Per scene TP/FP/FN, then:</p>
|
||
<ul>
|
||
<li><strong>Precision: STRICT.</strong> Any predicted actor not in the scene's X-Ray set is an FP,
|
||
<em>including out-of-cast confusions</em> (no gallery∩cast masking). An earlier
|
||
timepoint-sampled, cast-masked metric HID ~570 such FPs across 9 films and let the
|
||
optimizer drive <code>prob_threshold</code> to the 0.50 floor — a metric artifact. Counting
|
||
them is essential.</li>
|
||
<li><strong>Recall: FAIR.</strong> FN counts only X-Ray cast members <strong>who are in the gallery</strong>. 67%
|
||
of X-Ray cast (261/392) have no gallery reference embedding and can never be
|
||
recognised — counting them as misses penalises coverage, not the threshold. Both
|
||
<code>recall</code> (fair) and <code>recall_strict</code> (all) are reported.</li>
|
||
<li><strong>Aggregation:</strong> per-scene F1 → <strong>duration-weighted average within a movie</strong> (long
|
||
scenes count more) → <strong>equal-weight mean across movies</strong> (macro; each film counts
|
||
the same regardless of length). This is the DE objective.</li>
|
||
</ul>
|
||
<p>Implemented in <code>scripts/optimizer/scene_score.py</code> — since <strong>removed</strong> along
|
||
with this metric; its per-second successor is
|
||
<a href="https://gitea.tourolle.paris/dtourolle/scene-actor-extraction/raw/commit/4b5557974bef8783bacc375c0869e8f589d1b0a3/scripts/optimizer/second_score.py"><code>scripts/optimizer/second_score.py</code></a>
|
||
(see the <a href="../model-bakeoff/">bake-off round</a>).</p>
|
||
<h2 id="the-gallery-coverage-gap">The gallery coverage gap<a class="headerlink" href="#the-gallery-coverage-gap" title="Permanent link">¶</a></h2>
|
||
<p>Diagnosing low recall: only <strong>131 of 392</strong> X-Ray cast were in the gallery (33%). Every
|
||
in-gallery actor HAD embeddings (gallery well-formed) — the gap was pure coverage.
|
||
<a href="https://gitea.tourolle.paris/dtourolle/scene-actor-extraction/raw/commit/4b5557974bef8783bacc375c0869e8f589d1b0a3/scripts/optimizer/fetch_missing_actors.py"><code>scripts/optimizer/fetch_missing_actors.py</code></a>
|
||
recovers missing actors:
|
||
<code>nm-id → TMDB /find external_ids → /person/{id}/images → download → embed (sae_embed)</code>,
|
||
with a <code>--wikidata</code> fallback (P345→P18 Commons photo).</p>
|
||
<ul>
|
||
<li><strong>TMDB recovered 143/261</strong> (55%). 0 face-detection failures; the rest had no TMDB
|
||
person (60) or no profile photo (58). Coverage 33% → <strong>70%</strong>.</li>
|
||
<li><strong>Wikidata fallback: 0/118</strong> of the TMDB failures — only 4 even had a Commons photo,
|
||
none yielded a detectable face. → <strong>TheTVDB not worth pursuing</strong>: these remaining
|
||
actors are obscure enough that no image source covers them, AND (see below) most are
|
||
off-camera anyway.</li>
|
||
</ul>
|
||
<p><strong>Coverage vs detectability.</strong> Adding references lifted recall (58→68% at fixed config)
|
||
but modestly. Per-film drill-down (Lord of War: 12 actors recovered, only 1 had a
|
||
detectable on-camera face) showed most missing cast are a <strong>detectability gap</strong> — X-Ray
|
||
credits them as cast-in-scene (incl. off-camera/background), but their face never
|
||
appears clearly for the pipeline to detect. This is a fundamental ceiling of a
|
||
face-recognition pipeline vs X-Ray's presence semantics, not a fixable gap.</p>
|
||
<h2 id="optimizer">Optimizer<a class="headerlink" href="#optimizer" title="Permanent link">¶</a></h2>
|
||
<p><a href="https://gitea.tourolle.paris/dtourolle/scene-actor-extraction/raw/commit/4b5557974bef8783bacc375c0869e8f589d1b0a3/scripts/optimizer/optimize.py"><code>scripts/optimizer/optimize.py</code></a>
|
||
— scipy <code>differential_evolution</code> over the knob space,
|
||
each candidate = full replay of all films through the <strong>real</strong> C++ nodes (see the
|
||
KPN replay architecture below) scored by the metric above. Global objective (one
|
||
config for all films, not per-film).</p>
|
||
<p><strong>Convergence stability (augmented gallery, 233 evals):</strong></p>
|
||
<table>
|
||
<thead>
|
||
<tr>
|
||
<th>knob</th>
|
||
<th>top-20 range</th>
|
||
<th>verdict</th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr>
|
||
<td><code>prob_threshold</code></td>
|
||
<td>0.69–0.83 (σ 0.05)</td>
|
||
<td>TIGHT — trust 0.76</td>
|
||
</tr>
|
||
<tr>
|
||
<td><code>extinction_sec</code></td>
|
||
<td>1.0–2.2 (σ 0.33)</td>
|
||
<td>TIGHT — trust 1.5</td>
|
||
</tr>
|
||
<tr>
|
||
<td><code>anneal_sec</code></td>
|
||
<td>3.1–26.3 (σ 6.4)</td>
|
||
<td>LOOSE — insensitive, not hard-coded</td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
<p>F1 varied only 0.3pp across the top-20 → objective is flat near the optimum, so only
|
||
the tightly-converged knobs were adopted as defaults.</p>
|
||
<h2 id="replay-architecture-how-the-sweep-is-cheap">Replay architecture (how the sweep is cheap)<a class="headerlink" href="#replay-architecture-how-the-sweep-is-cheap" title="Permanent link">¶</a></h2>
|
||
<p>The optimizer never re-decodes video. <code>scene_analyze --dump-embeddings out.h5</code> runs the
|
||
expensive half once (decode→detect→align→embed) and dumps per-frame face embeddings
|
||
+ metadata to HDF5 (<a href="https://gitea.tourolle.paris/dtourolle/scene-actor-extraction/raw/commit/4b5557974bef8783bacc375c0869e8f589d1b0a3/scripts/optimizer/SCHEMA.md"><code>scripts/optimizer/SCHEMA.md</code></a>).
|
||
<a href="https://gitea.tourolle.paris/dtourolle/scene-actor-extraction/raw/commit/4b5557974bef8783bacc375c0869e8f589d1b0a3/scripts/optimizer/replay.py"><code>scripts/optimizer/replay.py</code></a> then
|
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replays that dump through the <strong>real</strong> C++ <code>face_tracker → identity_matcher →
|
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scene_tracker</code> assembled in a Python KPN network (<code>sae_kpn</code> nanobind module), varying
|
||
Config knobs freely — no GPU embedding, no decode. Verified BYTE-EXACT against
|
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<code>scene_analyze</code>'s own output. The dumps are gallery-independent, so testing the
|
||
augmented gallery needed no re-dump. <code>detector_conf</code> is replayable UPWARD only (the
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||
dump floor is 0.5).</p>
|
||
<h2 id="reproduce">Reproduce<a class="headerlink" href="#reproduce" title="Permanent link">¶</a></h2>
|
||
<div class="language-bash highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="c1"># 1. dump (once per film, needs video)</span>
|
||
</span><span id="__span-0-2"><a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a>scene_analyze<span class="w"> </span>--movie<span class="w"> </span><f><span class="w"> </span>--gallery<span class="w"> </span>gallery.json<span class="w"> </span>--dump-embeddings<span class="w"> </span>dump.h5<span class="w"> </span>--fps<span class="w"> </span><span class="m">1</span>
|
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</span><span id="__span-0-3"><a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a><span class="c1"># 2. build films manifest by Jellyfin ID join (see scripts/optimizer notes)</span>
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</span><span id="__span-0-4"><a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a><span class="c1"># 3. optimize</span>
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</span><span id="__span-0-5"><a id="__codelineno-0-5" name="__codelineno-0-5" href="#__codelineno-0-5"></a>python<span class="w"> </span>scripts/optimizer/optimize.py<span class="w"> </span>--manifest<span class="w"> </span>films.json<span class="w"> </span>--gallery<span class="w"> </span>gallery.json<span class="w"> </span><span class="se">\</span>
|
||
</span><span id="__span-0-6"><a id="__codelineno-0-6" name="__codelineno-0-6" href="#__codelineno-0-6"></a><span class="w"> </span>--params<span class="w"> </span>prob_threshold:0.5:0.999<span class="w"> </span>anneal_sec:1:30<span class="w"> </span>extinction_sec:1:15<span class="w"> </span><span class="se">\</span>
|
||
</span><span id="__span-0-7"><a id="__codelineno-0-7" name="__codelineno-0-7" href="#__codelineno-0-7"></a><span class="w"> </span>--popsize<span class="w"> </span><span class="m">8</span><span class="w"> </span>--maxiter<span class="w"> </span><span class="m">20</span><span class="w"> </span>--trajectory<span class="w"> </span>traj.jsonl<span class="w"> </span>--out<span class="w"> </span>opt.json
|
||
</span><span id="__span-0-8"><a id="__codelineno-0-8" name="__codelineno-0-8" href="#__codelineno-0-8"></a><span class="c1"># 4. score a fixed config / validate on a held-out set</span>
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||
</span><span id="__span-0-9"><a id="__codelineno-0-9" name="__codelineno-0-9" href="#__codelineno-0-9"></a><span class="c1"># (historical: score_config.py and scene_score.py were removed with the</span>
|
||
</span><span id="__span-0-10"><a id="__codelineno-0-10" name="__codelineno-0-10" href="#__codelineno-0-10"></a><span class="c1"># scene-union metric — use scripts/optimizer/second_score.py, per-second)</span>
|
||
</span><span id="__span-0-11"><a id="__codelineno-0-11" name="__codelineno-0-11" href="#__codelineno-0-11"></a>python<span class="w"> </span>scripts/optimizer/second_score.py<span class="w"> </span>--help
|
||
</span></code></pre></div>
|
||
<p>Superseded by the <a href="../model-bakeoff/">model bake-off + re-tune</a>, which
|
||
replaced this round's scene-union metric with per-second scoring.</p>
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