From 11a7e3ce2aaa4b0aae1c2ab637b7243c7d41b741 Mon Sep 17 00:00:00 2001 From: doma0211 Date: Tue, 26 Dec 2023 06:53:58 +0000 Subject: [PATCH] initialize page branch --- .vscode/settings.json | 3 + README.md | 3 - css/style.css | 41 ++++ images/architecture.png | Bin 0 -> 915668 bytes index.html | 403 ++++++++++++++++++++++++++++++++++++++++ js/main.js | 172 +++++++++++++++++ 6 files changed, 619 insertions(+), 3 deletions(-) create mode 100644 .vscode/settings.json create mode 100644 css/style.css create mode 100644 images/architecture.png create mode 100644 index.html create mode 100644 js/main.js diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..6f3a291 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,3 @@ +{ + "liveServer.settings.port": 5501 +} \ No newline at end of file diff --git a/README.md b/README.md index 9dcce62..5301458 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,2 @@ # Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Prior -Byeonghyeon Lee*, Howoong Lee*, Usman Ali†, and Eunbyung Park†, WACV 2024 - -Code comming soon!! diff --git a/css/style.css b/css/style.css new file mode 100644 index 0000000..a35701f --- /dev/null +++ b/css/style.css @@ -0,0 +1,41 @@ +.before, +.after { + margin: 0; +} + +.before figcaption, +.after figcaption { + background: #fff; + color: #2e3452; + opacity: 0.8; + padding: 12px; + position: absolute; + top: 10%; + transform: translateY(-50%); + line-height: 100%; + font-size: 18px; +} + +.before figcaption { + left: 12px; +} + +.after figcaption { + right: 12px; +} + +select { + margin: 0 auto; + color: #000000; + width: 160px; + height: 25px; + cursor: pointer; + text-align-last: center; + text-align: center; + -ms-text-align-last: center; + -moz-text-align-last: center; +} + +input { + width: 180px; +} \ No newline at end of file diff --git a/images/architecture.png b/images/architecture.png new file mode 100644 index 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HcmV?d00001 diff --git a/index.html b/index.html new file mode 100644 index 0000000..a2da4d3 --- /dev/null +++ b/index.html @@ -0,0 +1,403 @@ + + + + Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Prior + + + + + + + + + + + + + + + + + diff --git a/js/main.js b/js/main.js new file mode 100644 index 0000000..fd2e131 --- /dev/null +++ b/js/main.js @@ -0,0 +1,172 @@ +base_url = "https://huggingface.co/blee/Masked_Wavelet_Representation/resolve/main/images/" + +function select_model(target, dir, dataset, scene) { + if (dir == "left"){ + var img = document.getElementById("left_img" + "_" + dataset + "_" + scene); + var caption = document.getElementById("left_caption" + "_" + dataset + "_" + scene); + } + else if (dir == "right"){ + var img = document.getElementById("right_img" + "_" + dataset + "_" + scene); + var caption = document.getElementById("right_caption" + "_" + dataset + "_" + scene); + } + var model = target.value; + var frame = document.getElementById("input" + "_" + dataset + "_" + scene).value.toString().padStart(3, '0'); + + if (model == "TensoRF") + img.src = base_url + dataset + "/" + scene + "/" + "TensoRF" + "/" + frame + ".png" + else if (model == "GT") + img.src = base_url + dataset + "/" + scene + "/" + "GT" + "/" + frame + ".png" + else + img.src = base_url + dataset + "/" + scene + "/" + frame + "/" + model + ".png" + + caption.innerHTML = get_psnr(model, dataset, scene) +} + + +function select_frame(target, dataset, scene) { + var left_model = document.getElementById("left_select" + "_" + dataset + "_" + scene).value; + var right_model = document.getElementById("right_select" + "_" + dataset + "_" + scene).value; + + var left_img = document.getElementById("left_img" + "_" + dataset + "_" + scene); + var right_img = document.getElementById("right_img" + "_" + dataset + "_" + scene); + + var frame = target.value.toString().padStart(3, '0'); + + if (left_model == "TensoRF") + left_img.src = base_url + dataset + "/" + scene + "/" + "TensoRF" + "/" + frame + ".png" + else if (left_model == "GT") + left_img.src = base_url + dataset + "/" + scene + "/" + "GT" + "/" + frame + ".png" + else + left_img.src = base_url + dataset + "/" + scene + "/" + frame + "/" + left_model + ".png" + + if (right_model == "TensoRF") + right_img.src = base_url + dataset + "/" + scene + "/" + "TensoRF" + "/" + frame + ".png" + else if (right_model == "GT") + right_img.src = base_url + dataset + "/" + scene + "/" + "GT" + "/" + frame + ".png" + else + right_img.src = base_url + dataset + "/" + scene + "/" + frame + "/" + right_model + ".png" +} + +function get_psnr(model, dataset, scene) { + if (model == "TensoRF") { + if (dataset == "NSVF") { + if (scene == "Spaceship") + return "TensoRF-VM192
PSNR: 37.66" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "TensoRF-VM192
PSNR: 36.04
Size: 17.03MB" + } + } + } + else if (model == "GT") { + if (dataset == "NSVF") { + if (scene == "Spaceship") + return "TensoRF-VM192
PSNR: 37.66" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ground Truth" + } + } + } + else if(model == "1.6e-09") { + if(dataset == "NSVF") { + if(scene == "Spaceship") + return "Ours-Sparsity 0.9967
PSNR: 34.50" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9959
PSNR: 31.51
Size: 0.33MB" + } + } + } + else if(model == "8e-10") { + if(dataset == "NSVF") { + if(scene == "Spaceship") + return "Ours-Sparsity 0.9948
PSNR: 35.60" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9940
PSNR: 32.71
Size: 0.38MB" + } + } + } + else if(model == "4e-10") { + if(dataset == "NSVF") { + if(scene == "Spaceship") + return "Ours-Sparsity 0.9925
PSNR: 36.26" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9907
PSNR: 33.64
Size: 0.47MB" + } + } + } + else if(model == "2e-10") { + if(dataset == "NSVF") { + if(scene == "Spaceship") + return "Ours-Sparsity 0.9886
PSNR: 36.76" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9864
PSNR: 34.30
Size: 0.59MB" + } + } + } + else if(model == "1e-10"){ + if(dataset == "NSVF"){ + if(scene == "Spaceship") + return "Ours-Sparsity 0.9823
PSNR: 37.01" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9794
PSNR: 34.88
Size: 0.79MB" + } + } + } + else if(model == "5e-11"){ + if(dataset == "NSVF"){ + if(scene == "Spaceship") + return "Ours-Sparsity 0.9697
PSNR: 37.35" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9652
PSNR: 35.10
Size: 1.12MB" + } + } + } + else if(model == "2.5e-11"){ + if(dataset == "NSVF"){ + if(scene == "Spaceship") + return "Ours-Sparsity 0.9460
PSNR: 37.34" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9441
PSNR: 35.33
Size: 1.67MB" + } + } + } + else if(model == "1.25e-11"){ + if(dataset == "NSVF"){ + if(scene == "Spaceship") + return "Ours-Sparsity 0.9165
PSNR: 37.51" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.9165
PSNR: 35.44
Size: 2.33MB" + } + } + } + else if(model == "6.25e-12"){ + if(dataset == "NSVF"){ + if(scene == "Spaceship") + return "Ours-Sparsity 0.8876
PSNR: 37.61" + } + else if (dataset == "NeRF") { + if (scene == "Lego") { + return "Ours-Sparsity 0.8758
PSNR: 35.52
Size: 3.15MB" + } + } + } +}
+ + +
+ + +
+
+

Sharp-NeRF: Grid-based Fast Deblurring

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Neural Radiance Fields Using Sharpness Prior

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WACV 2024

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Byeonghyeon Lee1*, Howoong Lee1,2*, Usman Ali1†, and Eunbyung Park1†
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1Sungkyunkwan University, 2Hanwha Vision
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*Equal contribution, Corresponding authors
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[Code]   [Paper]

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Abstract

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Neural Radiance Fields (NeRF) has shown its remarkable performance in neural rendering-based novel view synthesis. However, NeRF suffers from severe visual quality degradation when the input images have been captured under imperfect conditions, such as poor illumination, defocus blurring and lens aberrations. Especially, defocus blur is quite common in the images when they are normally captured using cameras. Although few recent studies have proposed to render sharp images of considerably high-quality, yet they still face many key challenges. In particular, those methods have employed a Multi-Layer Perceptron (MLP) based NeRF which requires tremendous computational time. To overcome these shortcomings, this paper proposes a novel technique Sharp-NeRF---a grid-based NeRF that renders clean and sharp images from the input blurry images within a half an hour training. To do so, we used several grid-based kernels to accurately model the sharpness/blurriness of the scene. The sharpness level of the pixels is computed to learn the spatially varying blur kernels. We have conducted experiments on the benchmarks consisting of blurry images and have evaluated full-reference and non-reference metrics. The qualitative and quantitative results have revealed that our approach renders the sharp novel views with vivid colors and fine details, and it has considerably faster training time than the previous works.

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Bibtex

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+ We used the project page of Masked Wavelet Representation for Compact Neural Radiance Fields as a template. +

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