radi2025/slides.md

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title: "Enquêter sur les pipelines : une approche scientifique des organisations de production"
---


# Enquêter sur les pipelines

## une approche scientifique des organisations de production

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---

## À propos


<div id="left">

![](src/swann.png){.portrait}

### Dr. Swann Martinez 

</div>

<div id="right">

![](src/remy.png){.portrait}

### Dr. Rémy Sohier

</div>

note:
⏭️

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--

## Nos casquettes 🧢
<div id="left">
<img src="./src/xilam.png" width=40%><br>
<img src="./src/cube_nb.png" width=40%>
</div>

<div id="right">
<img src="./src/p8_logo.png" width=50%><br>
<img src="./src/inrev.png" width=30%>
</div>

note:
Swann est ingénieur R&D chez Cube/Xilam et a travaillé à temps partiel sur le projet en tant qu'ingénieur de recherche à l'INREV.  
Rémy est professeur et chercheur à l'INREV, responsable du programme Art & Technologie de l'Image à l'Université Paris 8.

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## Paneurama
<img src="./src/paneurama.png" width=10%/>
<img src="./src/funded_eu.png" width=25%/>
<br>

<img src="./src/Paneurama-partners-schools.png" width=70%/>
<br>

<img src="./src/Paneurama-partners-industry.png" width=90%/>
<br>

<img src="./src/Paneurama-partners-associated.png" width=90%/>

<br><br>


note:
This study was co-funded by Europe as part of an Erasmus+ project.<br>
BRIDGE THE GAP BETWEEN SCHOOLS AND STUDIOS<br>
Educational institutions<br>
Industry partners<br>
Associated partners in the Paneurama network<br>
BREDA -> Netherlands, Breda<br>
THE ANIMATION WORKSHOP -> Denmark, Viborg<br>
ANIMATIONINSTITUTE -> Germany, Stuttgart<br>
QVISTEN -> Norway
RISE FX -> Germany, Stuttgart  
Workshop, research, reports...

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---

## Sommaire

1. Constats & Motivations du projet {.fragment}
2. Démarche de recherche {.fragment}
3. Axes d'analyses{.fragment}
4. Limites & Futures{.fragment}

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note:
Aujourdhui, nous allons parler pipeline !

---

<!-- .slide: data-stack-name="Motivations" -->

# Constats

<!-- .slide: data-auto-animate data-transition-speed="slow"-->
<!-- 
    Parler des constats, des initiatives ont été prises:
    - pour définir certains termes
    - partager des outils / frameworks, etc.
    Mais à ce jours, 
    - peu de partage de données de fabrication
    - peu de recherche sur des cas d'études
 -->

--

<!-- .slide: data-transition="none" -->

### De nombreuses initiatives autour du pipeline ! 


<img src="./src/initiative_pipeline.drawio.svg" width=1000px/>

Et plein d'autres !
<!-- 
- Listes de partages (awesome-cg-vfx-pipeline,..)
- Définition de termes (lepipeline.org)
- Espaces de discussion (Discord,...)
- Conférences (TPC, DigiPro)
- Et plein d'autre... -->
<!-- TODO: Faire un zoli cercle -->


note:
Lorsque l'on cherche des connaissances et outils pipe. De nombreuses initiatives existent...
Mais Damien Coureau en parlera mieux dans la conférence suivante !

--

<!-- .slide: data-transition="none" -->

### Avec des résultats tangibles 

<img src="./src/initiative_pipeline_results.drawio.svg" width=1000px/>

<p>
<font color=red>--> Peu d'études de cas, pas d'études comparatives</font> 
</p>

note:
Cependant il est important de noter que parmis ces dernières, 
on a beaucoup d'outils <3, quelques articles mais peu de données précises sur les pipelines utilisés en production 
Avec le temps quelques initiative se sont figées faute de temps/moyen, les instigateurs se sont usés à la tache 

--

## Freins

- **Culturel**: pour beaucoup pipeline = secret professionnel
- **Temporel**: le temps manque entre deux productions pour partager, documenter les pratiques
- **Organique**: la nature évolutive complique 

note:
Avec le temps quelques initiative se sont figées faute de temps/moyen, les instigateurs se sont usés à la tache.

--

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## Approche académique ?

- Moyens publiques (temps)
- Neutralité
- Méthodologie scientifique

note:
Une approche académique porté par un laboratoire pourrait apporter une piste  de solution à ce manque d'analyse qualitatives. 

--

<!-- .slide: data-transition="none" -->

<img src="./src/initiative_pipeline.drawio.svg" width=1000px/>

note:

--

<img src="./src/initiative_pipeline_recherche.drawio.svg" width=1000px/>

note:

<!-- .slide: data-transition="none" -->

<!-- TODO: Mettre la bubule avec une cloques où on se situe -->

--

## Education

Combler un fossé entre l'éducation et l'industrie

- Fournir des données en phase avec la réalité  
- Faciliter l'intégration de nouveaux artistes

note:
Aider les étudiants et les écoles à comprendre comment les studios fonctionnent vraiment — et pas seulement la version idéalisée des manuels. <br>
Combler le fossé entre l'éducation et l'industrie : une meilleure formation facilite l'intégration des nouveaux artistes. <br>

--

## Recherche

Promouvoir la connaissance ouverte sur les pipelines
- Enrichir les méthodes cartographiques existentes
- Construire une cartograhie collective des pratiques de production

note:
Promouvoir la connaissance ouverte — partager les schémas de pipeline au lieu de les garder comme des « secrets de studio ». <br>
Construire une cartographie collective des pratiques de production que d'autres peuvent utiliser, enrichir ou remettre en question. <br>


---

<!-- .slide: data-stack-name="Méthode de recherche" -->

# Méthode de recherche

<!--  Comment on a mené cette recherche
-->
note:
Voyons maintenant **comment** nous avons abordé cela

--

## Problèmes

- Comment **visualiser** un pipeline ?
- Comment **comparer** les pipelines entre studios ?
<br>
<!-- TODO: Ameliorer schemas -->

<img src="./src/compare_studios.png" width="100%">

--

## Hypothèses

- Il existe quelque chose de **plus profond que le workflow**.
- Avec un **modèle de visualisation standard**, nous devrions pouvoir comparer les pipelines.
- Le pipeline pourrait être **non transférable** d'un studio à l'autre.

--

## Périmètre de l'étude

- Studios français (alumni)
- Animation 3D
- Studio avec un état d'esprit opensource


note:
Ces contraintes nous ont amenés à restreindre le périmètre de notre recherche.
Pour mener une étude comparative, nous nous sommes concentrés sur l'animation 3D.
Pour faciliter l'accès aux données et contourner les problèmes de confidentialité, nous avons privilégié les entreprises ayant une culture open source.

--

## Protocole de collecte des données

*- Comment récupérer et visualiser les informations sur les pipelines ? -*

note:
Le principal défi était de trouver un moyen de récupérer et de représenter les données des pipelines des studios ! Voyons comment nous avons procédé ⏭️

--

### Étape 1: <span class="fragment" data-fragment-index="0">Entretients semi-dirigés</span>

<div class="twocolumncenter">
<div>

- Cartographie des DCCs<sup>[1]</sup> {.fragment data-fragment-index="1"}
- Cartographie du workflow {.fragment data-fragment-index="2"}

<font size=50em color=red>**= Pourquoi**</font> {.fragment data-fragment-index="4"}
</div>
<div class="fragment" data-fragment-index="3">

![](./src/workflowdcc_carto_flavio.png)
*Schéma simplifié des départments & DCCs, Flavio Perez, 2017*
</div>

</div>

<div class="fragment footnote" data-fragment-index="1" >

- [1] Digital Content Creation tools
</div>


note:
La première étape consistait à comprendre la finalité du pipeline au sein de l'entreprise et à en obtenir une vue d'ensemble macro.<br>
Pour cela, lors de l'entretien, nous avons recensé les logiciels et les étapes de production, puis les avons cartographiés dans un schéma de base, inspiré des diagrammes de Flavio Perez dans son mémoire de master.<br>
Cela nous donne le "**POURQUOI**" du pipeline. ⏭️

--

<div class="schema">
    <img data-id="workflowcube" src="./src/chicky_workflow.svg" style="position:relative;" />
</div>

Résultat de l'interview semi-dirigée pour Cube Creative.

note:
Nous avons terminé le premier entretien avec des schémas comme celui-ci pour Cube Creative. ⏭️

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--

<div class="schema">
    <img data-id="workflowcube" src="./src/chicky_workflow.svg" style="position:relative;height:2000px;bottom:700px;right:-100px; max-width:none;" />
</div>

Une représentation simplifiée du workflow depuis l'écriture...

note:
Comme vous pouvez le voir, cela cartographie les étapes et logiciels, qu'ils soient intégrés ou non au pipeline, depuis l'écriture... ⏭️
<!-- .slide: data-auto-animate data-transition-speed="slow"-->

--

<div class="schema">
    <img data-id="workflowcube" src="./src/chicky_workflow.svg" style="position:relative;height:2000px;bottom:1300px;right:120px; max-width:none;" />
</div>

jusqu'à la fabrication des assets...

note:
jusqu'à la fabrication des assets... ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"-->

--

<div class="schema">
    <img data-id="workflowcube" src="./src/chicky_workflow.svg" style="position:relative;height:2000px;bottom:600px;right:2200px; max-width:none;" />
</div>

jusqu'à la fabrication des plans...

note:
jusqu'à la fabrication des plans... ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"-->

--

<div class="schema">
    <img data-id="workflowcube" src="./src/chicky_workflow.svg" style="position:relative;height:2000px;bottom:600px;right:3800px; max-width:none;" />
</div>

... jusqu'à la livraison des images 🚀 !

note:
... jusqu'à la livraison des images ⏭️

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--


### Étape 2: <span class="fragment" data-fragment-index="0">Entretiens dirigés</span>

<div style="text-align: center;">
<div class="fragment" style="display:inline;" data-fragment-index="1">Récupérer 
 <img style="vertical-align: middle;" width=4% src="./src/accolades_o.svg"></div>
<ul style="list-style-type: none; margin: 0; vertical-align: middle;text-align:center;">
<li data-fragment-index="2" class="fragment">niveaux d'infrastructure </li>
<li data-fragment-index="3" class="fragment">processus </li>
<li data-fragment-index="4" class="fragment">versionning </li>
<li data-fragment-index="5" class="fragment">compisition d'assets & shot</li>
<li data-fragment-index="6" class="fragment">formats de fichiers</li>
</ul>
<div class="fragment" data-fragment-index="7" style="display: inline;">
<img style="vertical-align: middle;" width=4% src="./src/accolades_c.svg">
pour comprendre <font color=red> <b>COMMENT</b></font> le pipeline est modélisé.
</div>
</div>

note:
L'objectif du processus de collecte des données :<br>
-Nous visons à obtenir une vue d'ensemble des motivations du pipeline <br>
-Nous définissons plus précisément sa gestion des données<br><br>
Cela nous donne le « comment » le pipeline est modélisé ==>  Mais alors, quelle représentation utiliser pour cartographier ces informations ? ...

--

## Étape 3: Méthodologie de cartographie du dataflow

--

### Pipeline Patterns <font size=6.6em><sup>[1][2]</sup></font>

<span data-id="pipeexplanation"><span class="fragment" data-fragment-index="0">Visualise comment <font color=red>**les données**</font></span> <span class="fragment" data-fragment-index="1"> changes à travers des <font color=red b>**processus**</font></span></span> <span class="fragment" data-fragment-index="2">selon un axe temporel et <font color=red> **d'infrastructure** </font>.</span>

<div class="r-stack">

<div>
<img src="./src/pipelinepatternlegend_elements.drawio.svg" class="fragment" data-fragment-index="0" width=900> 
<img src="./src/pipelinepatternlegend_relation.drawio.svg" class="fragment" data-fragment-index="1" width=800> 
</div>
<div>

![](./src/pipepattern_explanation.drawio.svg){.fragment data-fragment-index="2" height=600}

</div>
</div>

<div class="footnote">

- [1] B. Polson, « A conceptual framework for pipeline », in Proceedings of the 2015 Symposium on Digital Production, in DigiPro ’15. p. 51‑52. doi: 10.1145/2791261.2791272.
- [2] B. Polson, « CG pipeline design patterns », in Proceedings of the Fourth Symposium on Digital Production, in DigiPro ’14.p. 29. doi: 10.1145/2633374.2637729.
- More at https://www.pipelinepatterns.com/

</div>

note:
Pour cela, nous avons suivi la méthodologie proposée par Bill Polson sur **pipelinepatterns.com**.  
Cette approche consiste à représenter les éléments fondamentaux d'un pipeline et leurs relations... ⏭️
En résumé, il s'agit de montrer comment les données sont modifiées par les processus à travers le temps et l'infrastructure.
Et cela se passe en deux dimensions ! Verticalement, on a l'infrastructure, et horizontalement, le temps.<br>
Regardons un exemple issu du pipeline de Cube Creative ⏭️

<!-- .slide: data-auto-animate -->

--

<div class="schema">
    <img data-id="pipecube" src="./src/dataflow_cube_chicky.drawio.svg" style="position:relative;" />
</div>

*Dataflow utilisé sur la saison 4 de "Où est Ckicky ?" à Cube Creative.*

note:
Avec cette méthodologie, nous pouvons représenter le dataflow complet d'un pipeline.<br>
Regardons de plus près l'espace de travail de modélisation des assets ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"-->

--


<div class="schema">
    <img data-id="pipecube" src="./src/dataflow_cube_chicky_mask.drawio.svg" style="position:relative;height:2000px;bottom:1000px;right:400px; max-width:none;" />
</div>

*workspace de modélisation d'asset*

note:
On observe que Blender est utilisé pour cette étape de production. Sans surprise, la scène de travail ne contient que des informations de géométrie du point de vue du pipeline. Depuis Blender, les artistes exportent des playblasts à l'aide du processus *Tournette* (un addon interne) et modélisent les LODs via un *push*. ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"-->

--

<div class="schema">
    <img data-id="pipecube" src="./src/dataflow_cube_chicky.drawio.svg" style="position:relative;height:800px;right:-450px; max-width:none;" />
</div>

*workspace de modélisation d'asset*

note:
Comme vous pouvez le voir verticalement, ces éléments exportés sont synchronisés avec le serveur. Cependant, seuls le playblast et le fichier de travail sont versionnés ; les LODs ne le sont pas. ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"-->

--

<div class="schema">
    <img data-id="pipecube" src="./src/dataflow_cube_chicky.drawio.svg" style="height:800px; position:relative;right:300px; max-width:none;" />
</div>

*workspace de shading d'asset*

note:
Vient ensuite l'étape de shading... Malheureusement, il serait trop long d'expliquer en détail le dataflow de chaque étape.  
Retenez simplement que cette méthodologie a été utilisée pour modéliser les pipelines de tous les studios participants dès le début... ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow" -->

--

<div data-id="pipecube" class="schema">
    <img src="./src/dataflow_cube_chicky.drawio.svg" style="height:800px; position:relative;right:4900px; max-width:none;" />
</div>

*workspace de compositing de shot*

note:
..jusqu'à la fin du périmètre du pipeline.  

<!-- .slide: data-auto-animate data-transition-speed="slow" -->

---

<!-- .slide: data-stack-name="Participating studios" data-auto-animate data-transition-speed="slow"  -->

## Studios participants ❤️

<div class="threecolumn">

<div>
<img data-id="cubetrans" src="./src/cube.png" width=90% class="fragment"/>

<div>
Github link 👇

![](./src/cube_github.svg){width=300px .roundedcorner}

</div>

</div>
<div>
<img src="./src/autour-de-minuit.jpg" width=90% class="fragment"/>
<div>
Instance Gitea publique  👇

![](./src/adm_gitea.svg){width=300px .roundedcorner}

</div>

</div>
<div>
<img src="./src/Normaal.jpg" width= 90% class="fragment"/>
<div>
Stax Toolsuite 👇

![](./src/stax_link.svg){width=300px .roundedcorner}

</div>

</div>
</div>

note:
Présentons les studios qui ont gentiment accepté d'ouvrir leurs portes et de partager leurs pipelines :  
Cube Creative, Autour de Minuit et Normaal Animation. ⏭️

---

## Étude comparative

note:
**Now that** the introductions are done,  let's dive into the study 

<!-- .slide: data-stack-name="Comparative study" -->

--

## Projets étudiés

note:
**And we will firstly introduce** the projects that served as the basis for our pipeline mapping survey. ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

## Projets étudiés

<div class="threecolumn">

<div class="fragment">
<img src="./src/cube.png" width=50%/>
<img height=600 src="./src/where-s-chicky.jpg" />
</div>

<div class="fragment">
<img src="./src/autour-de-minuit.jpg" width=50%/>
<img height=600 src="./src/ohlala_adv.avif" />
</div>


<div class="fragment">
<img src="./src/Normaal.jpg" width=50%/>
<img height=600 src="./src/whooly_whooly.png" />
</div>

</div>

note:
**Pour Cube Creative**, nous avons étudié le pipeline de *Where's Chicky?*.  
**Pour Autour de Minuit**, nous avons cartographié leur nouvelle série en **pré-production**, *OhWow !*  
**Et pour Normaal**, nous avons documenté le pipeline utilisé pour la série TV Wooly Wooly.  
**Quelques notes** sur le format de ces projets ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

## Projets étudiés

<div class="threecolumn">

<div>
<img src="./src/cube.png" width=50%/>
<img height=400 src="./src/where-s-chicky.jpg" />

- format: **52x1" episodes**
- style: animation 3D

</div>

<div>
<img src="./src/autour-de-minuit.jpg" width=50%/>
<img height=400 src="./src/ohlala_adv.avif" />

- format: **52x7"  episodes**
- style: animation 3D

</div>


<div>
<img src="./src/Normaal.jpg" width=50%/>
<img height=400 src="./src/whooly_whooly.png" />

- format: **51x11" episodes**
- style: animation 3D

</div>

</div>

note:
**Les trois** projets sont des séries TV d'animation 3D destinées à la petite enfance.  
**Le format des projets** varie légèrement selon les productions, en particulier pour *Where's Chicky*.   
**À noter** que le pipeline de Chicky a également été utilisé pour leur nouvelle série, Piggy Builders (52x11"). 
**Nous allons** maintenant plonger progressivement dans les détails du pipeline de chaque production ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

# Productions steps: assets

| | |
|-|-|
| ![](./src/where-s-chicky.jpg){.portraitsquared} | <font class="fragment" size=50>Modeling ➡️ Shading ➡️ Rigging ➡️ Animation Bank (Characters)</font>  |
| ![](./src/ohlala_adv.avif){.portraitsquared} | <font class="fragment" size=50>Modeling ➡️ Surfacing ➡️ Setup</font> |
| ![](./src/whooly_whooly.png){.portraitsquared} |  <font class="fragment" size=50>Modeling ➡️ Surfacing ➡️ Setup</font> |

--

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

## <span data-id="test">Étapes de fabrication :</span> Shots

| | |
|-|-|
| ![](./src/where-s-chicky.jpg){.portraitsquared} | <font class="fragment" size=50>Layout ➡️ Animation ➡️ Rendering ➡️ Compositing </font>  |
| ![](./src/ohlala_adv.avif){.portraitsquared} | <font class="fragment" size=50>Layout ➡️ Animation ➡️ FX ➡️  Lighting </font> |
| ![](./src/whooly_whooly.png){.portraitsquared} |  <font class="fragment" size=50>Layout ➡️ Animation & FX ➡️ Rendering ➡️ <span class="fragment highlight-red">Compositing</span> ➡️ <span class="fragment highlight-red">editing</span></font> |

note:
For shot construction:  
**We have** ... for Chicky  
For OhLala: ...  
For Wooly Wooly: ...
Please note that compositing and editing are off-pipeline scope for *wooly wooly*.  
**The main difference** here is that, at Cube, FX are built as reusable assets instead of being created per shot.    
At ADM and Normaal, some FX are made directly in the shot.  
**Now,** which software is used for these steps? ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

## Outils de fabrication

<div class="threecolumn">

<div>

<img height=400 class="portraitsquared" src="./src/where-s-chicky.jpg" />

--- 
<div class="fragment">
<img src="./src/blender-icon-256x256-1.png" height=80/>
<img src="./src/logo-kitsu.de716c4b.png" height=80 />
<img src="./src/python-logo.png" height=80 />
<img src="./src/app-nuke-192x192.png" height=80/><br>
<img class="bw" src="./src/storyboard-pro-logo.png" height=80/>
</div>
</div>
<div>

<img height=400 class="portraitsquared" src="./src/ohlala_adv.avif" />

--- 
<div class="fragment">
<img src="./src/blender-icon-256x256-1.png" height=80/>
<img src="./src/logo-kitsu.de716c4b.png" height=80 />
<img src="./src/python-logo.png" height=80 /><br>
<img class="bw" src="./src/storyboard-pro-logo.png" height=80/>
</div>

</div>

<div>

<img height=400 class="portraitsquared" src="./src/whooly_whooly.png" />

--- 
<div class="fragment">
<img src="./src/blender-icon-256x256-1.png" height=80/>
<img src="./src/logo-kitsu.de716c4b.png" height=80 />
<img src="./src/python-logo.png" height=80 />
<img src="./src/ay-symbol-blackw-full.png" height=80 /><br>
<img class="bw" src="./src/storyboard-pro-logo.png" height=80/>
<img class="bw" src="./src/logo-adobe-after-effects-png_optimized-768x768.png" height=80/>
<img class="bw" src="./src/1200px-Adobe_Premiere_Pro_CC_icon.svg-1842527822.png" height=80/>
</div>
</div>

note:
**All three productions** use similar software environments, with some differences.     
**To improve clarity**, DCCs beyond the pipeline scope are shown in gray.   
On *Where's Chicky* ...  
On *OhWow* ...  
On *Wooly Wooly* ...        
**Storyboard Pro** is used in all three cases for storyboarding during pre-production.    
**For post-production**, Nuke and the Adobe suite are also used.   
**However**, Blender is the main 3D production tool for all three, and Kitsu is used for production tracking.   ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### Recapitulatifs du workflow simplifié

- Des formats de projets similaires{.fragment data-fragment-index="0" }
- Des étapes de fabrications similaires {.fragment data-fragment-index="1" }
- Des DCC's<sup>[1]</sup> similaires{.fragment data-fragment-index="2" }

<br>

<font color=red size=30 class="fragment">**Mais qu'en est-il du dataflow ?**</font>

<div class="fragment footnote" data-fragment-index="2" >

- [1] Digital Content Creation tools
</div>

note:
**To summarize** the details we just covered,  
we have three projects with similar formats, as well as similar production steps and DCCs.  
**But what** about the underlying dataflow? ⏭️

--

### Dataflow 

![](./src/underthehood.gif){width=700}

note:
What is fascinating about this study is that the mapped pipelines show some similarities, but above all, many differences. Especially in dataflows ⏭️

--

![](./src/dataflow_adv_holala_published.png)

![](./src/dataflow_cube_chicky_published.png)

![](./src/dataflow_normaal_wooly_wooly_published.png){width=1200}

note:
**I know** it's hard to see everything here ^^<br>
**But even from a distance**, you can visualize three **very** different dataflows! ⏭️

--

## Sudied aspects

Scene building strategies {.fragment}

<span data-id="worktitle">Asset update propagation patterns</span>{.fragment}

Infrastructure architecture {.fragment}

Standard file formats implications {.fragment}

Resource libraries{.fragment}

Work versionning strategies{.fragment}

Software environment{.fragment}

... {.fragment}

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

note:
**These mappings allowed us** to study many aspects of the audited pipelines!<br>
**Among these**, we have...<br>
**As we won't** have time to cover all these points in detail, we've selected the most significant one for this presentation. The full details will be published in an upcoming article. ⏭️

--

<span data-id="worktitle" style="font-size:1.8em;">Asset update propagation patterns</span>

*How update propagate through the fabrication ?*

note:
**Work propagation** is one of the most interesting aspects to study.  
In a pipeline, this term refers to how update propagate through the fabrication process. ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

## Tow mecanisms used
<div class="twocolumn">

<div class="fragment">

### ⬆️ Push{data-id="push"}
**Automatic** updates when an asset is published  
</div>

<div class="fragment">

### ⬇️ Pull
Updates applied **manually** from shots 
</div>
</div>

note:
**In the three pipelines studied,** we identified two main assets propagation patterns:<br>
-The Push, where updates are automatically propagated<br>
-The Pull, where updates are manually retrieved<br>
**Let’s take a closer** look at how this is modeled in a Blender dataflow... ⏭️

--

### ⬆️ Push : how ?

<div class="r-stack">

![](./src/push_0.drawio.svg){width=1600 .fragment current-visible data-fragment-index="0"}

![](./src/push_1.drawio.svg){width=1600 .fragment current-visible data-fragment-index="1"}

![](./src/push_2.drawio.svg){width=1600 .fragment current-visible data-fragment-index="2"}

![](./src/push_3.drawio.svg){width=1600 .fragment current-visible data-fragment-index="3"}

![](./src/push_4.drawio.svg){width=1600 .fragment current-visible data-fragment-index="4"}

![](./src/push_step_2_1.drawio.svg){width=1600 .fragment current-visible data-fragment-index="5"}

![](./src/push_step_2_2.drawio.svg){width=1600 .fragment current-visible data-fragment-index="6"}

![](./src/push_step_2_3.drawio.svg){width=1600 .fragment current-visible data-fragment-index="7"}

</div>

<div class="r-stack">

Asset latest state saved{ .fragment .current-visible data-fragment-index="2"}

Asset **hero version** linked in the layout scene during the **build**  {.fragment .current-visible data-fragment-index="3"}

Asset **hero version** linked in the animation scene during the **build**  {.fragment .current-visible data-fragment-index="4"}

Asset **hero version** <font color=red>**overwritten**</font> during the publish  {.fragment .current-visible data-fragment-index="6"}

Layout and Animation scene <font color=red>**automatically updated**</font> on loading.{.fragment .current-visible data-fragment-index="7"}


</div>

note:
**To simply explain** the push mechanism:  
**Imagine you have** an asset shading step, followed by layout and animation steps for shots.  
**The shading artist** works on the v1 version of the asset's shading.
**As the work progresses**, they publish (save as) the latest version in the "push zone / hero version."  
**Then** Layout and animation scenes are built by creating a **link** to this hero version.  
**With this setup,** whenever the shading artist creates a new version and updates the hero version, it is automatically propagated to all layout and animation shots using it !  
**This method is very convenient** for automatically updating scenes and fast iterations.    
**However,** automatic updates are not always desirable, as they can modify shots that have already been artistically approved.  
**But Where** is this mechanism used in the studied productions? ⏭️

--

### ⬆️ Push : Where ?

<div class="twocolumncenter">
<div class="fragment">
<img class="portraitsquared" src="./src/where-s-chicky.jpg"/><br>

- Method: Link 
- Scope: **Background** props assets, all steps

</div>

<div class="fragment">

<img class="portraitsquared" src="./src/whooly_whooly.png" /> <br>

- Method: Link & Overrides 
- Scope: All assets, Layout only
</div>

</div>

note:
**Push is used** by only two productions, and only partially.  
**In the case of Chicky**, the push is applied throughout the entire production chain, but only for one asset type: background components.  
**For Wooly Wooly**, the push is used for all assets up to the layout stage. Pull becomes the preferred method after layout, at the start of animation.  
**It's intersting** to see **where** but most of all to see **how** each studios implemented the method.
I will only show you a simplified view of it. 

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### ⬆️ Push : Implementations

<div class="twocolumntext">
<div>
<img class="portraitsquared" src="./src/where-s-chicky.jpg"/><br>
</div>
<div>

![](./src/push_chicky.svg){width=1000}

Chicky push example (*simplified*)
</div>

</div>

note:
**For Chicky,** the initial step of the push mechanism is still the publishing step. However, here, several versions of the same aspect of the asset are exported—these are called Level of Details (LODs).  
**As previously shown**, these LODs are then directly linked into the shot scenes.  
**The linked LOD version** is chosen based on the production step or the asset's distance from the camera.

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### ⬆️ Push : Implementations

<div class="twocolumntext">
<div>
<img class="portraitsquared" src="./src/whooly_whooly.png" /> <br>
</div>
<div>

![](./src/push_woolywooly.drawio.svg){width=1000}

Wooly Wooly push example (*Simplified*)

</div>

</div>

note:
**On Wooly Wooly**, the push mechanism is closer to the initial example we saw.  
**However, as you can see**, it’s not just a single hero version that gets published from the asset task.  
**Each publish iteration** is saved in the publish area,  
**but with every publish**, the hero version at the bottom is overwritten.  
**The published versions** are then used for the pull mechanism, which we’ll discuss next.  
**Now**, let's take a look at the *Pull* mechanism... ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### <span data-id="pull">⬇️ Pull :</span> How ?

<div class="r-stack">

![](./src/push_0.drawio.svg){width=1600 .fragment current-visible data-fragment-index="0"}

![](./src/push_1.drawio.svg){width=1600 .fragment current-visible data-fragment-index="1"}

![](./src/pull_0.drawio.svg){width=1600 .fragment current-visible data-fragment-index="2"}

![](./src/pull_1.drawio.svg){width=1600 .fragment current-visible data-fragment-index="3"}

![](./src/pull_2.drawio.svg){width=1600 .fragment current-visible data-fragment-index="4"}

![](./src/pull_3.drawio.svg){width=1600 .fragment current-visible data-fragment-index="5"}

</div>

<div class="r-stack">

Asset's **version** directly linked.{ .fragment .current-visible data-fragment-index="2"}

Updates are made <font color=red>**individually** in **shots** files</font> {.fragment .current-visible data-fragment-index="4"}

</div>

note:
**As usual,** the artist will start by creating a first version of an asset.
**The main difference with** the pull mechanism is that shot scenes have a specific asset version linked, rather than a single "hero" version that is regularly overwritten.    
**What does this** mean in practice? It simply reverses the update process !    
When a new version is published, each shot must be updated individually to point to the new asset version.  
**This process can be very tedious** to do manually, so studios often develop custom tools to automate it   
**Speaking of this,** lets see where the studio's used this mecanism... ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### <span data-id="pull">⬇️ Pull :</span> Where ? 

<div class="threecolumn">
<div class="fragment">

![](./src/whooly_whooly.png){.portraitsquared}

All assets from **animation** to **rendering** with link & overrides
</div>
<div class="fragment">

![](./src/where-s-chicky.jpg){.portraitsquared}

Character and Props in **all steps** with links
</div>
<div class="fragment">

![](./src/ohlala_adv.avif){.portraitsquared}

All asset in **all steps** with links + overrides
</div>

</div>

note:
**In the case of Wooly Wooly**, assets are "frozen" to the latest published version starting from the animation step. From that point on, asset updates are applied individually for each shot.<br>
**At Cube,** for Chicky, all animated assets use the pull mechanism from layout to rendering!       
**Finally,** for OhWow!, every production step relies on the pull approach. ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### ⬇️ Pull : Implementations

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

note:
**But how** the pull is implemented by each pipeline ? ⏭️

--

### ⬇️ Pull : Implementations

<div class="r-stack">
<img class="portraitsquared" src="./src/whooly_whooly.png" style="position:absolute;right:1500px;top:50%"/> <br>

![](./src/pull_woolywooly.drawio.svg){width=1000}
</div>

*Wooly Wooly* pull example (*Simplified*)


note:
**As see previously**, on *Wooly Wooly*, during asset publishing,   
the new asset version get's copied into the publish area and the hero one is overwritten.   
On their side, the main difference with the push lies in the linked blendfile: 
**Instead of pointing to the hero version**, it's points to the versionned file. ⏭️


<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### ⬇️ Pull : Implementations

<div class="r-stack">
<img class="portraitsquared" src="./src/where-s-chicky.jpg" style="position:absolute;right:1500px;top:50%"/> <br>


![](./src/pull_chicky.svg){width=1000}

</div>

*Where's chicky* pull example (*Simplified*)

note:
**In *Where's Chicky*,** the pull implementation doesn't use any links because library overrides wheren't trusted enough by the production.   
**So, instead of linking assets** in the shot scene as in the pull approach, assets are directly appended.     
**It means that** the assets lives directly in shot scenes, and a new append is neeeded for each update. 

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### ⬇️ Pull : Implementations

<div class="r-stack">
<img class="portraitsquared" src="./src/ohlala_adv.avif" style="position:absolute;right:1500px;top:50%"/> <br>

![](./src/pull_ohlala.drawio.svg){width=1000}


</div>

*Ohlala!* pull example (*Simplified*)

note:
**Finally, on Ohlala,** asset working versions are directly linked into shot scenes.  
**This requires artists** to be highly disciplined in organizing their scenes, as there is no the safety margin of the publish area.    
**On the other hand,** this approach greatly reduces disk space usage since data is not duplicated. ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

## Assets updates propagation : Recap'

*Three strategies to do it*

<div class="threecolumn">

<div class="fragment">

![](./src/where-s-chicky.jpg){.portraitsquared}

--- 
- **Push** for static assets.
- **Pull** for animated assets 

---
<font color=red> = Per-asset type strategy</font>

</div>

<div class="fragment">

![](./src/ohlala_adv.avif){.portraitsquared}

--- 
- **Pull** accross all the production

---
<font color=red> = Global strategy</font>

</div>
<div class="fragment">


![](./src/whooly_whooly.png){.portraitsquared}

--- 
- **Push** for all asset until Layout
- **Pull**  from Animation

---
<font color=red> = Per-step strategy</font>

</div>
</div>

note:
**À quick recap of** propagation strategies per production  
**On Chickies,** the push is mainly used for static assets, pull for animated assets    
**On holala,** the pull is used everywhere    
**And finally,** we have an hybrid strategy per shot step for wooly wooly. ⏭️

--


### Push 🆚 Pull 

<div class="twocolumncenter">

<div class="fragment">

<span style="font-size:2em;">**+**</span>

Support asset's fast iteration

Reduce development effort

<span style="font-size:2em;">**-**</span>

Less control over updates propagation

Require a good communication

</div>

<div class="fragment">

<span style="font-size:2em;">**+**</span>

Update control granularity

Better history tracking

<span style="font-size:2em;">**-**</span>

Require tools developments

Slow asset iteration
 
</div>

</div>

note:
**Let's briefly** look at some advantages and disadvantages of these two complementary methods.<br>
**On one hand,** the push supports fast asset iteration, but it does not allow for granular control over updates in shot files—pull is preferable here.     
**On the other hand pull makes it easier** to respect a validation chain.<br>
**From a purely technical perspective**, the pull requires more development effort, since updating references means opening scenes and changing links.  
**The Push pattern relies entirely on Blender's** native mechanisms and therefore requires very little development from the pipeline team.<br>

---

<!-- .slide: data-stack-name="Final thoughts" -->

## Final thoughts

note:
**Unfortunately,** we won't have time today to go further into the details of the data we collected.  
**However,** feel free to come see us after the presentation if you would like more information.   
**Before we finish,** let's look at the limitations and future directions of this study ⏭️

<!-- .slide: data-auto-animate data-transition-speed="slow"  -->

--

### Mapping methodology limits

- Validation data
- Attributes overrides
- Production tracker

note:
First of all, it's important to note that the mapping methodology we used for dataflow did not provide a way to represent Blender's override mechanism.  
It also did not address the role of the production tracker.  
We therefore extended the set of our diagrams to include these two elements.  
We plan to share a library of shapes for drawio/diagram.net to make it easier to create these diagrams. ⏭️

--

### Data sample limits

- Only french studios
- Only TV Show projects

note:
Initially, the study focused on a small group of companies to explore the project's feasibility. Additionally, we only examined TV series projects. ⏭️

--

### Futures

- Interview european studio's {.fragment}
- Map other project formats (movies, VFX, games) {.fragment} 
- Bring interactive online visualisation of studied pipelines {.fragment}  

note:
In the future, we hope to broaden the scope of this study by surveying European studios to understand how socio-economic factors in different countries impact pipeline structures.<br>
We also aim to map pipelines used in other project formats to compare their structures.<br>
Improving the accessibility of these mappings is another major focus. ⏭️


--

## Thanks you !

<div id="left">

### 📧 Participate to the study

![](./src/mail.svg){width=300}
</div>

<div id="right">

### ❤️ Thanks to the contributors

- Félix David (Normaal)
- Christophe Seux (ADM)
- Florentin Luce (ADM)
- Axel Tillement (Cube)


</div>

note:
Thanks a lot for listening !
If you represent a studio and are interested in participating, feel free to come talk to us directly or send an email to this address!  
Don't hesitate to reach out if you have any questions!