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<!doctype html>
<html lang="en">
<head>
<title>NerfBaselines: Method NeRF-W (reimplementation)</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="icon" href="/favicon.ico" type="image/x-icon" sizes="256x256">
<link href="/styles.css" rel="stylesheet">
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@100..900&display=swap" rel="stylesheet">
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<script src="/scripts.js" defer></script>
</head>
<body class="main-container">
<main>
<div class="results-page__header">
<h1>
NeRF-W (reimplementation)<a class="text-blue" href="javascript:history.back()"><i class="ti ti-arrow-back-up"></i></a>
</h1>
<p class="text-justify">
Unofficial reimplementation of NeRF-W. Does not reach the performance reported in the original paper, but is widely used for benchmarking.
</p>
</div>
<div id=phototourism class="result-set-panel">
<div class="result-set-panel__header">
<h2>
Photo Tourism
</h2>
<p class="text-justify">Photo Tourism is a dataset of images of famous landmarks, such as the Sacre Coeur, the Trevi Fountain, and the Brandenburg Gate. The images were captured by tourist at different times of the day and year, images have varying lighting conditions and occlusions. The evaluation protocol is based on NeRF-W, where the image appearance embeddings are optimized on the left side of the image and the metrics are computed on the right side of the image.</p>
</div>
<div class="table-container">
<table class="table">
<thead class="table__header">
<th class="w70"></th>
<th class="w120"><span class="table__sortbutton" title="Sort by scene (ascending)">Scene <i class="ti" /></span></th>
<th><span class="table__sortbutton" title="Sort by PSNR (ascending)">PSNR <i class="ti" /></span></th>
<th><span class="table__sortbutton" title="Sort by SSIM (ascending)">SSIM <i class="ti" /></span></th>
<th><span class="table__sortbutton" title="Sort by LPIPS (ascending)">LPIPS <i class="ti" /></span></th>
<th><span class="table__sortbutton" title="Sort by time (ascending)">Time <i class="ti" /></span></th>
<th><span class="table__sortbutton" title="Sort by GPU mem. (ascending)">GPU mem. <i class="ti" /></span></th>
</thead>
<tbody class="expand-root">
<tr>
<td class="w70">
<a href="https://huggingface.co/nerfbaselines/nerfbaselines/resolve/main/nerfw-reimpl/phototourism/sacre-coeur.zip" title="Download checkpoint and predictions for scene Sacre Coeur" class="ti table__action ti-download ti-blue"></a>
</td>
<td data-sort-value="1" class="w120">Sacre Coeur</td>
<td data-sort-value="6"><span class="table__allowcopy">19.56</span>
</td>
<td data-sort-value="4"><span class="table__allowcopy">0.795</span>
</td>
<td data-sort-value="13"><span class="table__allowcopy">0.260</span>
</td>
<td data-sort-value="15"><span class="table__allowcopy">41h 41m 36s</span>
</td>
<td data-sort-value="15"><span class="table__allowcopy">98.80 GB</span>
</td>
</tr>
<tr>
<td class="w70">
<a href="https://huggingface.co/nerfbaselines/nerfbaselines/resolve/main/nerfw-reimpl/phototourism/trevi-fountain.zip" title="Download checkpoint and predictions for scene Trevi Fountain" class="ti table__action ti-download ti-blue"></a>
</td>
<td data-sort-value="2" class="w120">Trevi Fountain</td>
<td data-sort-value="7"><span class="table__allowcopy">21.48</span>
</td>
<td data-sort-value="3"><span class="table__allowcopy">0.693</span>
</td>
<td data-sort-value="14"><span class="table__allowcopy">0.331</span>
</td>
<td data-sort-value="17"><span class="table__allowcopy">49h 43m 22s</span>
</td>
<td data-sort-value="17"><span class="table__allowcopy">98.81 GB</span>
</td>
</tr>
<tr>
<td class="w70">
<a href="https://huggingface.co/nerfbaselines/nerfbaselines/resolve/main/nerfw-reimpl/phototourism/brandenburg-gate.zip" title="Download checkpoint and predictions for scene Brandenburg Gate" class="ti table__action ti-download ti-blue"></a>
</td>
<td data-sort-value="0" class="w120">Brandenburg Gate</td>
<td data-sort-value="8"><span class="table__allowcopy">24.22</span>
</td>
<td data-sort-value="5"><span class="table__allowcopy">0.884</span>
</td>
<td data-sort-value="12"><span class="table__allowcopy">0.213</span>
</td>
<td data-sort-value="16"><span class="table__allowcopy">41h 46m 21s</span>
</td>
<td data-sort-value="16"><span class="table__allowcopy">98.80 GB</span>
</td>
</tr>
</tbody>
<tfoot>
<tr>
<td class="w70"></td>
<td class="w120">Average</td>
<td><span class="table__allowcopy">21.75</span>
</td>
<td><span class="table__allowcopy">0.790</span>
</td>
<td><span class="table__allowcopy">0.268</span>
</td>
<td><span class="table__allowcopy">44h 23m 46s</span>
</td>
<td><span class="table__allowcopy">98.80 GB</span>
</td>
</tr>
</table>
</div>
</div>
</main>
</body>
</html>