Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches
The emerging trend of AR/VR places great demands on 3D content. However, most existing software requires expertise and is difficult for novice users to use. In this paper, we aim to create sketch-based modeling tools for user-friendly 3D modeling. We introduce Reality3DSketch with a novel applicatio...
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creator | Chen, Tianrun Ding, Chaotao Zhu, Lanyun Zang, Ying Liao, Yiyi Li, Zejian Sun, Lingyun |
description | The emerging trend of AR/VR places great demands on 3D content. However, most
existing software requires expertise and is difficult for novice users to use.
In this paper, we aim to create sketch-based modeling tools for user-friendly
3D modeling. We introduce Reality3DSketch with a novel application of an
immersive 3D modeling experience, in which a user can capture the surrounding
scene using a monocular RGB camera and can draw a single sketch of an object in
the real-time reconstructed 3D scene. A 3D object is generated and placed in
the desired location, enabled by our novel neural network with the input of a
single sketch. Our neural network can predict the pose of a drawing and can
turn a single sketch into a 3D model with view and structural awareness, which
addresses the challenge of sparse sketch input and view ambiguity. We conducted
extensive experiments synthetic and real-world datasets and achieved
state-of-the-art (SOTA) results in both sketch view estimation and 3D modeling
performance. According to our user study, our method of performing 3D modeling
in a scene is $>$5x faster than conventional methods. Users are also more
satisfied with the generated 3D model than the results of existing methods. |
doi_str_mv | 10.48550/arxiv.2310.18148 |
format | Article |
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existing software requires expertise and is difficult for novice users to use.
In this paper, we aim to create sketch-based modeling tools for user-friendly
3D modeling. We introduce Reality3DSketch with a novel application of an
immersive 3D modeling experience, in which a user can capture the surrounding
scene using a monocular RGB camera and can draw a single sketch of an object in
the real-time reconstructed 3D scene. A 3D object is generated and placed in
the desired location, enabled by our novel neural network with the input of a
single sketch. Our neural network can predict the pose of a drawing and can
turn a single sketch into a 3D model with view and structural awareness, which
addresses the challenge of sparse sketch input and view ambiguity. We conducted
extensive experiments synthetic and real-world datasets and achieved
state-of-the-art (SOTA) results in both sketch view estimation and 3D modeling
performance. According to our user study, our method of performing 3D modeling
in a scene is $>$5x faster than conventional methods. Users are also more
satisfied with the generated 3D model than the results of existing methods.</description><identifier>DOI: 10.48550/arxiv.2310.18148</identifier><language>eng</language><subject>Computer Science - Human-Computer Interaction</subject><creationdate>2023-10</creationdate><rights>http://creativecommons.org/licenses/by-nc-nd/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,781,886</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2310.18148$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2310.18148$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Tianrun</creatorcontrib><creatorcontrib>Ding, Chaotao</creatorcontrib><creatorcontrib>Zhu, Lanyun</creatorcontrib><creatorcontrib>Zang, Ying</creatorcontrib><creatorcontrib>Liao, Yiyi</creatorcontrib><creatorcontrib>Li, Zejian</creatorcontrib><creatorcontrib>Sun, Lingyun</creatorcontrib><title>Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches</title><description>The emerging trend of AR/VR places great demands on 3D content. However, most
existing software requires expertise and is difficult for novice users to use.
In this paper, we aim to create sketch-based modeling tools for user-friendly
3D modeling. We introduce Reality3DSketch with a novel application of an
immersive 3D modeling experience, in which a user can capture the surrounding
scene using a monocular RGB camera and can draw a single sketch of an object in
the real-time reconstructed 3D scene. A 3D object is generated and placed in
the desired location, enabled by our novel neural network with the input of a
single sketch. Our neural network can predict the pose of a drawing and can
turn a single sketch into a 3D model with view and structural awareness, which
addresses the challenge of sparse sketch input and view ambiguity. We conducted
extensive experiments synthetic and real-world datasets and achieved
state-of-the-art (SOTA) results in both sketch view estimation and 3D modeling
performance. According to our user study, our method of performing 3D modeling
in a scene is $>$5x faster than conventional methods. Users are also more
satisfied with the generated 3D model than the results of existing methods.</description><subject>Computer Science - Human-Computer Interaction</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj8FOAjEURbtxYcAPcOX7gcHptJ122BkQNWBIgP3ktX2V6sCQzsTI3zuCq5uc5N7cw9g9zyfSKJU_YvqJ35NCDIAbLs0tW24Im9ifxXz7Rb3bT2GDp-hBzOG99dTE4we0Adb2k1zfQUjtAbYDbAgWiWiPRw_XJnVjdhOw6ejuP0dst3jezV6z1frlbfa0yrDUJiOpisopi0byXJVaBO6F46WvdOErZQltGL7K4FFxrQsrFVXcOI1eUNBejNjDdfZiU59SPGA6139W9cVK_AK01Ea6</recordid><startdate>20231027</startdate><enddate>20231027</enddate><creator>Chen, Tianrun</creator><creator>Ding, Chaotao</creator><creator>Zhu, Lanyun</creator><creator>Zang, Ying</creator><creator>Liao, Yiyi</creator><creator>Li, Zejian</creator><creator>Sun, Lingyun</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20231027</creationdate><title>Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches</title><author>Chen, Tianrun ; Ding, Chaotao ; Zhu, Lanyun ; Zang, Ying ; Liao, Yiyi ; Li, Zejian ; Sun, Lingyun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a678-e4529c5ba84105673f1d3c16d972d95beabf5504fda51772b45e918c7ad3ef7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Computer Science - Human-Computer Interaction</topic><toplevel>online_resources</toplevel><creatorcontrib>Chen, Tianrun</creatorcontrib><creatorcontrib>Ding, Chaotao</creatorcontrib><creatorcontrib>Zhu, Lanyun</creatorcontrib><creatorcontrib>Zang, Ying</creatorcontrib><creatorcontrib>Liao, Yiyi</creatorcontrib><creatorcontrib>Li, Zejian</creatorcontrib><creatorcontrib>Sun, Lingyun</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chen, Tianrun</au><au>Ding, Chaotao</au><au>Zhu, Lanyun</au><au>Zang, Ying</au><au>Liao, Yiyi</au><au>Li, Zejian</au><au>Sun, Lingyun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches</atitle><date>2023-10-27</date><risdate>2023</risdate><abstract>The emerging trend of AR/VR places great demands on 3D content. However, most
existing software requires expertise and is difficult for novice users to use.
In this paper, we aim to create sketch-based modeling tools for user-friendly
3D modeling. We introduce Reality3DSketch with a novel application of an
immersive 3D modeling experience, in which a user can capture the surrounding
scene using a monocular RGB camera and can draw a single sketch of an object in
the real-time reconstructed 3D scene. A 3D object is generated and placed in
the desired location, enabled by our novel neural network with the input of a
single sketch. Our neural network can predict the pose of a drawing and can
turn a single sketch into a 3D model with view and structural awareness, which
addresses the challenge of sparse sketch input and view ambiguity. We conducted
extensive experiments synthetic and real-world datasets and achieved
state-of-the-art (SOTA) results in both sketch view estimation and 3D modeling
performance. According to our user study, our method of performing 3D modeling
in a scene is $>$5x faster than conventional methods. Users are also more
satisfied with the generated 3D model than the results of existing methods.</abstract><doi>10.48550/arxiv.2310.18148</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Human-Computer Interaction |
title | Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches |
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