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LVFace Deep Dive
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<h1 id="deep-dive-lvface-b-glint360k">Deep dive: LVFace-B Glint360K<a class="headerlink" href="#deep-dive-lvface-b-glint360k" title="Permanent link">&para;</a></h1>
<p>LVFace won the model bake-off (see <a href="../best-model/">Which model is best?</a>) and is
the shipped default embedder. This page is the honest accounting of how it
actually performs — what a good second looks like, where the errors actually
come from, and two cases where the ground truth itself is wrong and LVFace is
right.</p>
<div class="admonition note">
<p class="admonition-title">How to read the frames on this page</p>
<p>The top is the film frame, with a box and name on every face the pipeline
identified. The bottom panels are the per-second verdict against X-Ray:
<strong>Onscreen</strong> lists faces named in the frame, <strong>Offscreen</strong> lists cast
X-Ray marks present in the scene without a visible face — presence
carried by the tracker's windows, not by a detection. Colors are the
score: <span style="color:#0ca30c"><strong>green</strong></span> = correct (TPI),
<span style="color:#eb6834"><strong>orange</strong></span> = wrong (FPI),
<span style="color:#3987e5"><strong>blue</strong></span> = missed (FN).</p>
</div>
<h2 id="what-good-looks-like">What good looks like<a class="headerlink" href="#what-good-looks-like" title="Permanent link">&para;</a></h2>
<p><img alt="Wedding couple correctly identified, Downton Abbey: A New Era" src="../assets/images/downton_wedding_couple.jpg" /></p>
<p>Six faces on screen, all six named correctly — including Penelope Wilton at the
edge of the pews and a half-occluded Michelle Dockery — while thirteen more
cast members X-Ray marks present in the scene are correctly carried as
"Offscreen" by their presence windows. One miss in the whole frame: Maggie
Smith (blue). Score for this second: 0.86.</p>
<p><img alt="19 of 20 correct in the funeral crowd" src="../assets/images/downton_funeral_19of20.jpg" /></p>
<p>The same film's funeral gathering: mourning dress, hats, half the faces turned.
<strong>Nineteen of the twenty cast X-Ray lists for this scene are scored correctly</strong>
— seven named on screen at up to 100% confidence, twelve more correctly held
as present off-screen.</p>
<p>And the pipeline doesn't need the face to be <em>real</em>:</p>
<p><img alt="Herbie Hancock identified on an in-fiction video call" src="../assets/images/valerian_screen_call.jpg" /></p>
<p>That's Herbie Hancock at 98% — as a face on a <em>screen inside the movie</em>, over a
sci-fi HUD overlay, during a video call in Valerian. A face is a face, whether
it's in the room or on the bridge's comms display.</p>
<h2 id="training-vs-held-out-the-generalization-gap">Training vs. held-out: the generalization gap<a class="headerlink" href="#training-vs-held-out-the-generalization-gap" title="Permanent link">&para;</a></h2>
<p>The shipped config (<code>prob_threshold=0.754, anneal_sec=35.54,
extinction_sec=57.43, expand_gallery=true</code>) was tuned against 4 films. Scored
against the 5 films the optimizer never saw:</p>
<p><img alt="Held-out per-film F1 vs. the training-set fit" src="../assets/images/holdout_f1_by_film.png" /></p>
<table>
<thead>
<tr>
<th>film</th>
<th>F1</th>
<th>P</th>
<th>R</th>
<th>TPI</th>
<th>FPI</th>
<th>misid</th>
<th>FN</th>
</tr>
</thead>
<tbody>
<tr>
<td>Benny &amp; Joon</td>
<td>83.0%</td>
<td>89.1%</td>
<td>77.7%</td>
<td>15125</td>
<td>1846</td>
<td>0</td>
<td>4337</td>
</tr>
<tr>
<td>Lovelace</td>
<td>77.5%</td>
<td>90.3%</td>
<td>67.9%</td>
<td>14990</td>
<td>1085</td>
<td>58</td>
<td>7085</td>
</tr>
<tr>
<td>Valerian and the City of a Thousand Planets</td>
<td>74.1%</td>
<td>97.1%</td>
<td>60.0%</td>
<td>18663</td>
<td>548</td>
<td>0</td>
<td>12467</td>
</tr>
<tr>
<td>Downton Abbey: A New Era</td>
<td>56.2%</td>
<td>97.8%</td>
<td>39.4%</td>
<td>52027</td>
<td>1173</td>
<td>0</td>
<td>80084</td>
</tr>
<tr>
<td><strong>The Many Saints of Newark</strong></td>
<td><strong>46.3%</strong></td>
<td><strong>54.7%</strong></td>
<td>40.1%</td>
<td>15922</td>
<td>4394</td>
<td><strong>974</strong></td>
<td>23791</td>
</tr>
<tr>
<td><strong>macro average</strong></td>
<td><strong>67.4%</strong></td>
<td>85.8%</td>
<td>57.0%</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
</tbody>
</table>
<p><strong>67.4% held-out vs. 75.3% on training</strong> — an ~8pp drop, and a <strong>37pp spread
between the best and worst held-out film</strong>. The config does not generalize
uniformly, and the spread traces to two mechanisms, both visible frame by
frame below.</p>
<h2 id="mechanism-1-extinction-bridging-usually-right-wrong-at-hard-cuts">Mechanism 1: extinction bridging — usually right, wrong at hard cuts<a class="headerlink" href="#mechanism-1-extinction-bridging-usually-right-wrong-at-hard-cuts" title="Permanent link">&para;</a></h2>
<p>The extinction window keeps an identity alive through seconds where no face is
detectable. <strong>Most of the time this is exactly what you want</strong>, and it's where
a lot of the TPI count comes from:</p>
<p><img alt="Two faces on screen, six more correctly bridged" src="../assets/images/lovelace_polygraph_bridged.jpg" /></p>
<p>Lovelace's polygraph scene: only Eric Roberts and Amanda Seyfried have visible
faces, but X-Ray lists eight cast present — and all eight score green, the
other six correctly carried by presence windows through a scene where the
camera never shows them. A perfect second, and the extinction/anneal machinery
is <em>why</em>.</p>
<p>The same mechanism has a failure case: a hard cut into long faceless footage.
Both Many Saints of Newark (974 misIDs) and Downton Abbey (FN=80084, the worst
recall of the five) are dominated by it — verified directly against the raw
per-frame stream and the HDF5 dump's own detection counts, not inferred from
the score alone. <strong>This is not a malfunction</strong>: the tracker is doing exactly
what its window is for; the footage just stops cooperating. In the debug
overlay (which draws a bridged identity's last-known bbox, unlike the shipped
output, which emits presence windows and no boxes at all) the bridged state is
visible spatially:</p>
<p><img alt="Debug overlay: bridged identities drawn at their last-known positions" src="../assets/images/many_saints_ghost_fpi.jpg" />
<em>Debug-overlay rendering (<code>dump_error_frames.py --raw</code>): "Jon Bernthal", "Joey
Diaz" and "Billy Magnussen" are extinction-bridged identities from the previous
shot, drawn frozen over the wall and the hanging plates. Frame
<code>many_saints/fpi/fpi_t03543.jpg</code>, <code>montage-frames</code> artifact package.</em></p>
<p>The cost is measurable, not just visible. Downton Abbey's hard cut into its
closing credits, plotting the dump's own per-second <code>face_count</code> (detector
output, independent of the tracker) against what the tracker reports:</p>
<p><img alt="Detector vs. tracker through Downton Abbey's cut to credits" src="../assets/images/downton_ghost_timeline.png" /></p>
<p>From the cut onward the detector sees <strong>zero faces for nearly a minute</strong> — and
the tracker keeps reporting the last shot's 15 identities the whole time
(verified for Hugh Bonneville: bbox <code>(1743.2, 0.0, 171.3, 317.8)</code>, unchanged to
the pixel, at every sampled second for 57+ seconds). The staircase at the right
edge is the extinction window expiring actor by actor. That plateau is
<code>SceneTrackerFunc::active_[actor_idx].last_bbox</code>
(<a href="https://gitea.tourolle.paris/dtourolle/scene-actor-extraction/raw/commit/4b5557974bef8783bacc375c0869e8f589d1b0a3/src/nodes/scene_tracker_node.hpp"><code>src/nodes/scene_tracker_node.hpp</code></a>)
re-emitted as designed: <code>extinction_sec=57.4</code> was tuned long because bridging
wins on most footage (see the polygraph frame above) — the training films just
never contained a faceless stretch long enough to show the cost side, and the
held-out set did.</p>
<p>The same track-continuation machinery has one milder spatial artifact, worth
knowing when reading these frames:</p>
<p><img alt="Two labels on one face after a shot/reverse-shot cut" src="../assets/images/cafe_society_rapid_cut.jpg" />
<em>Café Society (a training film), a shot/reverse-shot dialog: that is Steve
Carell wearing both his own label and Jesse Eisenberg's.</em></p>
<p>At a rapid cut, the previous shot's track can linger for a beat at nearly the
same screen position the new face occupies — here Jesse Eisenberg's box from
the counter-shot lands on Steve Carell. Note what the score panel says,
though: both actors are green, because both <em>are</em> present in this dialog
scene per X-Ray. The spatial label is briefly wrong; the per-second presence
claim — the thing the pipeline actually ships — is right. It's the same trade
as the extinction window: track continuation smooths over cuts, and 1 fps
sampling occasionally catches the seam.</p>
<h2 id="mechanism-2-the-face-vs-presence-ceiling">Mechanism 2: the face-vs-presence ceiling<a class="headerlink" href="#mechanism-2-the-face-vs-presence-ceiling" title="Permanent link">&para;</a></h2>
<p>Downton Abbey's recall didn't collapse because faces were misread — it
collapsed because for most of its 80084 FN-seconds there was <strong>no face to
read</strong>:</p>
<p><img alt="22 cast credited, nobody facing the camera" src="../assets/images/downton_crew_fn.jpg" /></p>
<p>A newsreel crew hauls equipment through the hall: X-Ray credits 22 cast as
present in this scene; not one face looks at the camera. Eight are still
scored green (windows bridging from adjacent shots) — the other fourteen are
blue FNs that no face-recognition pipeline could ever recover. X-Ray encodes
<em>scene membership</em>; the pipeline measures <em>on-screen faces</em>. In ensemble films
those two definitions diverge massively, and that gap — not identification
error — is most of what the FN column counts.</p>
<p><img alt="Presence without a detectable face, The Many Saints of Newark" src="../assets/images/many_saints_outofcast_fpi.jpg" /></p>
<p>Same ceiling from the other side: Michela De Rossi in frame but turned away,
five cast correctly bridged as offscreen (green), four blue FNs — and one
orange we'll come back to below.</p>
<h2 id="where-lvface-beat-x-ray">Where LVFace beat X-Ray<a class="headerlink" href="#where-lvface-beat-x-ray" title="Permanent link">&para;</a></h2>
<p>Not every orange in these frames is actually wrong.
<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>
scores strictly against X-Ray — but X-Ray itself has holes, and the pipeline
found two kinds.</p>
<p><img alt="LVFace correctly identifies Germar Terrell Gardner, uncredited by X-Ray" src="../assets/images/germar_beats_xray.jpg" /></p>
<p>Germar Terrell Gardner — a real, clean, high-confidence detection — is counted
as an out-of-cast misID because he doesn't appear in X-Ray's <code>people.csv</code> for
The Many Saints of Newark at all. But Jellyfin's independent cast metadata
<em>does</em> credit him for this exact film (cross-checked via
<code>experiments/manifests/jellyfin_casts.json</code> from the <code>experiment-data</code> artifact
package, a completely separate data source from X-Ray). That's also him in
orange in the frame above — every one of those "errors" is the pipeline being
right about a person X-Ray forgot.</p>
<p><img alt="Robert Patrick, clearly on screen, scored wrong by a ground-truth gap" src="../assets/images/lovelace_robert_patrick_fpi.jpg" /></p>
<p>And it isn't only uncredited bit-parts. That is <strong>Robert Patrick</strong> — top-billed
in Lovelace, unmistakably on screen, reading his newspaper, identified at
100% — scored orange because X-Ray's people-in-scene list for <em>this scene</em>
doesn't include him. The identification is flawless; the ground truth missed
an actor sitting in the middle of the frame.</p>
<p>This doesn't mean every flagged misID is secretly correct — Many Saints'
974-count total is still overwhelmingly extinction bridging at cuts, not
uncredited cameos. But the X-Ray corpus is a convenient, large-scale ground
truth, not a perfect one, and the misID/FPI numbers in these tables carry an
irreducible noise floor from ground-truth gaps in both directions.</p>
<h2 id="summary">Summary<a class="headerlink" href="#summary" title="Permanent link">&para;</a></h2>
<p>LVFace is the right default: it wins the model comparison outright, it names
19 of 20 correctly across a hat-heavy funeral crowd, and it recognises a face
on a screen inside the movie. Its error budget decomposes into two understood
mechanisms — extinction bridging at hard cuts (a tunable trade, not a bug) and
the face-vs-presence ceiling baked into X-Ray's semantics — plus a nonzero
slice where the pipeline is right and the ground truth is wrong. The held-out
generalization gap (75.3% → 67.4%) is real and should be treated as the honest
expected performance, not the training-set number.</p>
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