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<title>NeRFsPP2024</title>
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<section class="hero">
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<h1 class="title is-1 publication-title"> Evaluating Neural Radiance Fields for 3D PlantGeometry Reconstruction in Field Conditions</h1>
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<a href="https://www.linkedin.com/in/arbab-arshad/" target="_blank">Muhammad Arbab Arshad,</a>
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<span class="author-block">
<a href="https://www.linkedin.com/in/talukder-zaki-jubery-23322551/" target="_blank">Talukder Zaki Jubery,</a>
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<a href="https://www.linkedin.com/in/james-afful-745247179/" target="_blank">James Afful,</a>
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<a href="https://www.linkedin.com/in/anushrutjignasu/" target="_blank">Anushrut Jignasu,</a>
</span>


<span class="author-block">
<a href="https://www.engineering.iastate.edu/people/profile/baskarg/" target="_blank">Baskar Ganapathysubramanian,</a>
</span>

<span class="author-block">
<a href="https://www.engineering.iastate.edu/people/profile/soumiks/" target="_blank">Soumik Sarkar,</a>
</span>
<span class="author-block">
<a href="https://www.engineering.iastate.edu/people/profile/adarsh/" target="_blank">Adarsh Krishnamurthy</a>
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<span class="author-block">Iowa State University <br>

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<a href="https://spj.science.org/doi/epdf/10.34133/plantphenomics.0235" target="_blank" class="external-link button is-normal is-rounded is-dark">
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<i class="fas fa-file-pdf"></i>
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<span>Paper</span>
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<a href=" https://github.com/idealab-isu/Evaluate-NeRFs-for-Plants" target="_blank" class="external-link button is-normal is-rounded is-dark">
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<i class="fab fa-github"></i>
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<span>Code</span>
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<a href="https://github.com/idealab-isu/Evaluate-NeRFs-for-Plants/tree/main/Dataset" target="_blank" class="external-link button is-normal is-rounded is-dark">
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<span>Dataset</span>
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<h2 class="subtitle has-text-centered">
<b>Overview of the NeRFs</b>NeRFs are proposed as an alternative to traditional TLS scans for 3D plant reconstruction, offering cost-effective and efficient modeling from images captured at multipleangles using a smartphone camera, in contrast to the higher expense and extensive processing time required by TLS for multiangle scan registration.
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<h2 class="title is-3">Abstract</h2>
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<p>

We evaluate different Neural Radiance Field (NeRF) techniques for the 3D reconstruction of plants invaried environments, from indoor settings to outdoor fields. Traditional methods usually fail to capture thecomplex geometric details of plants, which is crucial for phenotyping and breeding studies. We evaluatethe reconstruction fidelity of NeRFs in 3 scenarios with increasing complexity and compare the resultswith the point cloud obtained using light detection and ranging as ground truth. In the most realistic fieldscenario, the NeRF models achieve a 74.6% F1 score after 30 min of training on the graphics processingunit, highlighting the efficacy of NeRFs for 3D reconstruction in challenging environments. Additionally, wepropose an early stopping technique for NeRF training that almost halves the training time while achievingonly a reduction of 7.4% in the average F1 score. This optimization process substantially enhances thespeed and efficiency of 3D reconstruction using NeRFs. Our findings demonstrate the potential of NeRFsin detailed and realistic 3D plant reconstruction and suggest practical approaches for enhancing thespeed and efficiency of NeRFs in the 3D reconstruction process. </p>
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<h2 class="title is-3" style="margin: 0;">Dataset Features</h2>
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Example images input to NeRFs for reconstruction across 3 different scenarios. (A) Scenario I: Indoor single object. (B) Scenario II: Indoor multiple objects. (C) Scenario III:Outdoor scene

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Workflow for 3D reconstruction and evaluation.
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<h2 class="title is-4">Results</h2>
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<p>
Precision-recall curves for the three scenarios based on varying distance thresholds after 30,000 iterations (Scenarios I and II) and 60,000 iterations (Scenario III)for (A) Instant-NGP, (B) TensoRF, and (C) NeRFacto
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<span class="dvima">Team</span>
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<a href="https://www.linkedin.com/in/arbab-arshad/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/Arbab.png" alt="" style="width: 90%;" />
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<span style="font-weight: bold;">Muhammad Arbab Arshad</span>
</a>
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<a href="https://www.linkedin.com/in/talukder-zaki-jubery-23322551/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/Zaki1.png" alt="" style="width: 90%;" />
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<span style="font-weight: bold;">Talukder Zaki Jubery</span>
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<a href="https://www.linkedin.com/in/james-afful-745247179/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/James.jpeg" alt="James Afful" style="width: 90%;" />
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<span style="font-weight: bold;">James Afful</span>
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<a href="https://www.linkedin.com/in/anushrutjignasu/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/anshu.jpeg" alt="Anushrut Jignasu" style="width: 90%;" />
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<span style="font-weight: bold;">Anushrut Jignasu</span>
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<a href="https://www.engineering.iastate.edu/people/profile/baskarg/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/Baskar.png" alt="" style="width: 88%;" />
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<span style="font-weight: bold;">Baskar Ganapathysubramanian</span>
</a>
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<a href="https://www.engineering.iastate.edu/people/profile/soumiks/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/Soumik1.png" alt="" style="width: 92%;" />
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<span style="font-weight: bold;">Soumik Sarkar</span>
</a>
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<!-- Team Member 10 -->
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<a href="https://www.engineering.iastate.edu/people/profile/adarsh/" target="_blank" style="border-bottom: none;">
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<img src="static/images/team/Adarsh.png" alt="" style="width: 90%;" />
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<span style="font-weight: bold;">Adarsh Krishnamurthy</span>
</a>
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