We are happy to announce that we are hiring a Product Engineer in Rennes, France, to help transform our on-the-fly 3D Gaussian Splatting reconstruction research into a startup!
Details and application: jobs.inria.fr/public/class...
In our #SIGGRAPH2025 paper “Interactive Optimization of Scaffolded Procedural Patterns”, we introduce a new way to define and optimize procedural patterns in a sketch-based interactive design workflow.
Moving to sustainable manufacturing requires new computational design tools. We show how to make new objects from old "trash". 🚮
Presented on Thursday at SGP 2025 in the Fabrication session.
![MOTIVATION
Graphical Processing Units (GPUs) are at the core of Computer Graphics research. These chips are critical for rendering images, processing geometric data, and training machine learning models. Yet, the production and disposal of GPUs emits CO2 and results in toxic e-waste [1].
METHOD
We surveyed 888 papers presented at SIGGRAPH (premier conference for computer graphics research), from 2018 to 2024, and systematically gathered GPU models cited in the text.
We then contextualize the hardware reported in papers with publicly available data of consumers’ hardware [2, 3].
REFERENCES
[1] CRAWFORD, KATE. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2021.
[2] STEAM. Steam Hardware Survey. https://store.steampowered.com/hwsurvey
[3] BLENDER. Blender Open Data. https://opendata.blender.org](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:gpta66q3ots5ia23kvfzpu5r/bafkreidqnyftshkcmtpzqlxsknnvcn34xszafururgdixddtcuzrmwloqq@jpeg)
MOTIVATION Graphical Processing Units (GPUs) are at the core of Computer Graphics research. These chips are critical for rendering images, processing geometric data, and training machine learning models. Yet, the production and disposal of GPUs emits CO2 and results in toxic e-waste [1]. METHOD We surveyed 888 papers presented at SIGGRAPH (premier conference for computer graphics research), from 2018 to 2024, and systematically gathered GPU models cited in the text. We then contextualize the hardware reported in papers with publicly available data of consumers’ hardware [2, 3]. REFERENCES [1] CRAWFORD, KATE. The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2021. [2] STEAM. Steam Hardware Survey. https://store.steampowered.com/hwsurvey [3] BLENDER. Blender Open Data. https://opendata.blender.org
Ever wondered how badly we're all addicted to buying new GPUs in graphics labs?
Come see our talk at #SIGGRAPH2025 to discuss how we can collectively move "Towards a sustainable use of GPUs in Graphics Research"
with @elie-michel.bsky.social @axelparis.bsky.social Octave Crespel and Felix Hähnlein
Excited to share our paper, "Splat and Replace: 3D Reconstruction with Repetitive Elements", which I'll be presenting at #SIGGRAPH2025!
Project page: repo-sam.inria.fr/nerphys/spla...
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We are very excited to announce our work "On-the-fly Reconstruction for Large-Scale Novel View Synthesis from Unposed Images", to be presented at #SIGGRAPH2025!
Learn more: repo-sam.inria.fr/nerphys/on-t...
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