Zero-shot CAD Program Re-Parameterization for Interactive Manipulation
Parametric CAD models encode entire families of shapes that should, in principle, be easy for designers to explore. However, in practice, parametric CAD models can be difficult to manipulate due to implicit semantic constraints among parameter values. Finding and enforcing these semantic constraints...
Gespeichert in:
Hauptverfasser: | , , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | Kodnongbua, Milin Jones, Benjamin T Ahmad, Maaz Bin Safeer Kim, Vladimir G Schulz, Adriana |
description | Parametric CAD models encode entire families of shapes that should, in
principle, be easy for designers to explore. However, in practice, parametric
CAD models can be difficult to manipulate due to implicit semantic constraints
among parameter values. Finding and enforcing these semantic constraints solely
from geometry or programmatic shape representations is not possible because
these constraints ultimately reflect design intent. They are informed by the
designer's experience and semantics in the real world. To address this
challenge, we introduce a zero-shot pipeline that leverages pre-trained large
language and image model to infer meaningful space of variations for a shape.
We then re-parameterize a new constrained parametric CAD program that captures
these variations, enabling effortless exploration of the design space along
meaningful design axes. |
doi_str_mv | 10.48550/arxiv.2306.03217 |
format | Article |
fullrecord | <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2306_03217</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2306_03217</sourcerecordid><originalsourceid>FETCH-LOGICAL-a677-ccab7377b920b65183796bcde2f32bcfd13391b2fbc51c55cec8a11fa3aee643</originalsourceid><addsrcrecordid>eNotj8FKAzEURbNxIdUPcGV-IGOS1yQzyzJaLbRY1JWb4SV90UA7KelY1K-3jq7u5R64cBi7UrKa1sbIGyyf6VhpkLaSoJU7Z_NXKlkc3vPA29ktX5f8VnDHn0is8VRooJK-cUi55zEXvuhPA4YhHYmvsE_7j-0IL9hZxO2BLv9zwp7ndy_tg1g-3i_a2VKgdU6EgN6Bc77R0lujanCN9WFDOoL2IW4UQKO8jj4YFYwJFGpUKiIgkZ3ChF3_vY4e3b6kHZav7tenG33gB84NRpA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Zero-shot CAD Program Re-Parameterization for Interactive Manipulation</title><source>arXiv.org</source><creator>Kodnongbua, Milin ; Jones, Benjamin T ; Ahmad, Maaz Bin Safeer ; Kim, Vladimir G ; Schulz, Adriana</creator><creatorcontrib>Kodnongbua, Milin ; Jones, Benjamin T ; Ahmad, Maaz Bin Safeer ; Kim, Vladimir G ; Schulz, Adriana</creatorcontrib><description>Parametric CAD models encode entire families of shapes that should, in
principle, be easy for designers to explore. However, in practice, parametric
CAD models can be difficult to manipulate due to implicit semantic constraints
among parameter values. Finding and enforcing these semantic constraints solely
from geometry or programmatic shape representations is not possible because
these constraints ultimately reflect design intent. They are informed by the
designer's experience and semantics in the real world. To address this
challenge, we introduce a zero-shot pipeline that leverages pre-trained large
language and image model to infer meaningful space of variations for a shape.
We then re-parameterize a new constrained parametric CAD program that captures
these variations, enabling effortless exploration of the design space along
meaningful design axes.</description><identifier>DOI: 10.48550/arxiv.2306.03217</identifier><language>eng</language><subject>Computer Science - Graphics</subject><creationdate>2023-06</creationdate><rights>http://creativecommons.org/licenses/by-nc-sa/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2306.03217$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2306.03217$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Kodnongbua, Milin</creatorcontrib><creatorcontrib>Jones, Benjamin T</creatorcontrib><creatorcontrib>Ahmad, Maaz Bin Safeer</creatorcontrib><creatorcontrib>Kim, Vladimir G</creatorcontrib><creatorcontrib>Schulz, Adriana</creatorcontrib><title>Zero-shot CAD Program Re-Parameterization for Interactive Manipulation</title><description>Parametric CAD models encode entire families of shapes that should, in
principle, be easy for designers to explore. However, in practice, parametric
CAD models can be difficult to manipulate due to implicit semantic constraints
among parameter values. Finding and enforcing these semantic constraints solely
from geometry or programmatic shape representations is not possible because
these constraints ultimately reflect design intent. They are informed by the
designer's experience and semantics in the real world. To address this
challenge, we introduce a zero-shot pipeline that leverages pre-trained large
language and image model to infer meaningful space of variations for a shape.
We then re-parameterize a new constrained parametric CAD program that captures
these variations, enabling effortless exploration of the design space along
meaningful design axes.</description><subject>Computer Science - Graphics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj8FKAzEURbNxIdUPcGV-IGOS1yQzyzJaLbRY1JWb4SV90UA7KelY1K-3jq7u5R64cBi7UrKa1sbIGyyf6VhpkLaSoJU7Z_NXKlkc3vPA29ktX5f8VnDHn0is8VRooJK-cUi55zEXvuhPA4YhHYmvsE_7j-0IL9hZxO2BLv9zwp7ndy_tg1g-3i_a2VKgdU6EgN6Bc77R0lujanCN9WFDOoL2IW4UQKO8jj4YFYwJFGpUKiIgkZ3ChF3_vY4e3b6kHZav7tenG33gB84NRpA</recordid><startdate>20230605</startdate><enddate>20230605</enddate><creator>Kodnongbua, Milin</creator><creator>Jones, Benjamin T</creator><creator>Ahmad, Maaz Bin Safeer</creator><creator>Kim, Vladimir G</creator><creator>Schulz, Adriana</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20230605</creationdate><title>Zero-shot CAD Program Re-Parameterization for Interactive Manipulation</title><author>Kodnongbua, Milin ; Jones, Benjamin T ; Ahmad, Maaz Bin Safeer ; Kim, Vladimir G ; Schulz, Adriana</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a677-ccab7377b920b65183796bcde2f32bcfd13391b2fbc51c55cec8a11fa3aee643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Computer Science - Graphics</topic><toplevel>online_resources</toplevel><creatorcontrib>Kodnongbua, Milin</creatorcontrib><creatorcontrib>Jones, Benjamin T</creatorcontrib><creatorcontrib>Ahmad, Maaz Bin Safeer</creatorcontrib><creatorcontrib>Kim, Vladimir G</creatorcontrib><creatorcontrib>Schulz, Adriana</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kodnongbua, Milin</au><au>Jones, Benjamin T</au><au>Ahmad, Maaz Bin Safeer</au><au>Kim, Vladimir G</au><au>Schulz, Adriana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Zero-shot CAD Program Re-Parameterization for Interactive Manipulation</atitle><date>2023-06-05</date><risdate>2023</risdate><abstract>Parametric CAD models encode entire families of shapes that should, in
principle, be easy for designers to explore. However, in practice, parametric
CAD models can be difficult to manipulate due to implicit semantic constraints
among parameter values. Finding and enforcing these semantic constraints solely
from geometry or programmatic shape representations is not possible because
these constraints ultimately reflect design intent. They are informed by the
designer's experience and semantics in the real world. To address this
challenge, we introduce a zero-shot pipeline that leverages pre-trained large
language and image model to infer meaningful space of variations for a shape.
We then re-parameterize a new constrained parametric CAD program that captures
these variations, enabling effortless exploration of the design space along
meaningful design axes.</abstract><doi>10.48550/arxiv.2306.03217</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | DOI: 10.48550/arxiv.2306.03217 |
ispartof | |
issn | |
language | eng |
recordid | cdi_arxiv_primary_2306_03217 |
source | arXiv.org |
subjects | Computer Science - Graphics |
title | Zero-shot CAD Program Re-Parameterization for Interactive Manipulation |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T09%3A26%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Zero-shot%20CAD%20Program%20Re-Parameterization%20for%20Interactive%20Manipulation&rft.au=Kodnongbua,%20Milin&rft.date=2023-06-05&rft_id=info:doi/10.48550/arxiv.2306.03217&rft_dat=%3Carxiv_GOX%3E2306_03217%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |