{"id":11485,"date":"2023-01-07T21:53:00","date_gmt":"2023-01-07T13:53:00","guid":{"rendered":"http:\/\/139.9.1.231\/?p=11485"},"modified":"2023-02-01T10:18:42","modified_gmt":"2023-02-01T02:18:42","slug":"mine","status":"publish","type":"post","link":"http:\/\/139.9.1.231\/index.php\/2023\/01\/07\/mine\/","title":{"rendered":"MINE&#8211;\u5229\u7528\u5355\u5f20\u56fe\u7247\u505a\u4e09\u7ef4\u91cd\u5efa"},"content":{"rendered":"\n<h3>\u7aef\u5230\u7aef\u7c7b\u578b<\/h3>\n\n\n\n<p>                    <a href=\"https:\/\/zhuanlan.zhihu.com\/p\/360467357\" target=\"_blank\" rel=\"noreferrer noopener\"> <strong> \u7528MPI\uff08Multi-Plane Image \uff09\u4ee3\u66ffNeRF\u7684RGB\u03c3\u4f5c\u4e3a\u7f51\u7edc\u7684\u8f93\u51fa<\/strong><\/a><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"1024\" height=\"515\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-1-1024x515.png\" alt=\"\" class=\"wp-image-11503\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-1-1024x515.png 1024w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-1-300x151.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-1-768x386.png 768w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-1.png 1122w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>     \u6765\u81ea\u5b57\u8282\u8df3\u52a8\u89c6\u89c9\u6280\u672f\u56e2\u961f\u7684\u7814\u7a76\u8005\u5c06 NeRF \u548c Multiplane Image\uff08MPI\uff09\u7ed3\u5408\uff0c\u63d0\u51fa\u4e86\u4e00\u79cd\u65b0\u7684\u4e09\u7ef4\u7a7a\u95f4\u8868\u8fbe\u65b9\u5f0f MINE\u3002\u8be5\u65b9\u6cd5\u901a\u8fc7\u5bf9\u5355\u5f20\u56fe\u7247\u505a\u4e09\u7ef4\u91cd\u5efa\uff0c\u5b9e\u73b0\u65b0\u89c6\u89d2\u5408\u6210\u548c\u6df1\u5ea6\u4f30\u7b97\u3002<\/p>\n\n\n\n<p><strong><em>\u5f00\u6e90\u4e86\u8bad\u7ec3\u4ee3\u7801\uff08\u57fa\u4e8eLLFF\u6570\u636e\u96c6\u7684toy example\uff09\uff0cpaper\u91cc\u9762\u6570\u636e\u96c6\u7684pretrained models\uff0c\u5e76\u63d0\u4f9b\u4e86demo\u4ee3\u7801\uff1a<\/em><\/strong><\/p>\n\n\n\n<ul class=\"has-bright-blue-background-color has-background\"><li><strong>\u8bba\u6587\u5730\u5740\uff1a<a href=\"https:\/\/arxiv.org\/pdf\/2103.14910.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/arxiv.org\/pdf\/2103.14910.pdf<\/a><\/strong><\/li><li><strong>\u9879\u76ee\u5730\u5740\uff1a<a href=\"https:\/\/github.com\/vincentfung13\/MINE\">https:\/\/github.com\/vincentfung13\/MINE<\/a><\/strong><\/li><\/ul>\n\n\n\n<p><strong>\u76f8\u5173\u5de5\u4f5c<\/strong><\/p>\n\n\n\n<p>        \u8fd1\u5e74\u6765\uff0c\u5728\u65b0\u89c6\u89d2\u5408\u6210\u8fd9\u4e2a\u9886\u57df\u91cc\uff0c\u6700\u706b\u7206\u7684\u65b9\u6cd5\u65e0\u7591\u662f ECCV 2020 \u7684 NeRF [5]\u3002\u4e0e\u4f20\u7edf\u7684\u4e00\u4e9b\u624b\u5de5\u8bbe\u8ba1\u7684\u663e\u5f0f\u4e09\u7ef4\u8868\u8fbe\uff08Light Fields\uff0cLDI\uff0cMPI \u7b49\uff09\u4e0d\u540c\uff0cNeRF \u628a\u6574\u4e2a\u4e09\u7ef4\u7a7a\u95f4\u7684\u51e0\u4f55\u4fe1\u606f\u4e0e texture \u4fe1\u606f\u5168\u90e8\u7528\u4e00\u4e2a MLP \u7684\u6743\u91cd\u6765\u8868\u8fbe\uff0c\u8f93\u5165\u4efb\u610f\u4e00\u4e2a\u7a7a\u95f4\u5750\u6807\u4ee5\u53ca\u89c2\u5bdf\u89d2\u5ea6\uff0cMLP \u4f1a\u9884\u6d4b\u4e00\u4e2a RGB \u503c\u548c volume density\u3002\u76ee\u6807\u56fe\u7247\u7684\u6e32\u67d3\u901a\u8fc7 ray tracing \u548c volume rendering \u7684\u65b9\u5f0f\u6765\u5b8c\u6210\u3002\u5c3d\u7ba1 NeRF \u7684\u6548\u679c\u975e\u5e38\u60ca\u8273\uff0c\u4f46\u5b83\u7684\u7f3a\u70b9\u4e5f\u975e\u5e38\u660e\u663e\uff1a<\/p>\n\n\n\n<ol><li><strong>\u4e00\u4e2a\u6a21\u578b\u53ea\u80fd\u8868\u8fbe\u4e00\u4e2a\u573a\u666f\uff0c\u4e14\u4f18\u5316\u4e00\u4e2a\u573a\u666f\u8017\u65f6\u4e45\uff1b<\/strong><\/li><li><strong>per-pixel \u6e32\u67d3\u8f83\u4e3a\u4f4e\u6548\uff1b<\/strong><\/li><li><strong>\u6cdb\u5316\u80fd\u529b\u8f83\u5dee\uff0c\u4e00\u4e2a\u573a\u666f\u9700\u8981\u8f83\u591a\u7684\u7167\u7247\u624d\u80fd\u8bad\u7ec3\u597d\u3002<\/strong><\/li><\/ol>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p5.itc.cn\/images01\/20211009\/9513da5943944cfb8ad5d5b4b1cb6275.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>     <strong>\u53e6\u5916\u4e00\u4e2a\u4e0e\u8be5\u7814\u7a76\u8f83\u76f8\u5173\u7684\u662f MPI\uff08Multiplane Image\uff09[1, 2, 3]\u3002MPI \u5305\u542b\u4e86\u591a\u4e2a\u5e73\u9762\u7684 RGB-alpha \u56fe\u7247\uff0c\u5176\u4e2d\u6bcf\u4e2a\u5e73\u9762\u8868\u8fbe\u573a\u666f\u5728\u67d0\u4e2a\u6df1\u5ea6\u4e2d\u7684\u5185\u5bb9\uff0c\u5b83\u7684\u4e3b\u8981\u7f3a\u70b9\u5728\u4e8e\u6df1\u5ea6\u662f\u56fa\u5b9a\u53ca\u79bb\u6563\u7684\uff0c\u8fd9\u4e2a\u7f3a\u70b9\u9650\u5236\u4e86\u5b83\u5bf9\u4e09\u7ef4\u7a7a\u95f4\u7684\u8868\u8fbe\u80fd\u529b\u3002[1, 2, 3] \u90fd\u80fd\u65b9\u4fbf\u5730\u6cdb\u5316\u5230\u4e0d\u540c\u7684\u573a\u666f\uff0c\u7136\u800c MPI \u5404\u4e2a\u5e73\u9762\u7684\u6df1\u5ea6\u662f\u56fa\u5b9a\u4e14\u79bb\u6563\u7684\uff0c\u8fd9\u4e2a\u7f3a\u70b9\u4e25\u91cd\u9650\u5236\u4e86\u5b83\u7684\u6548\u679c\u3002<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p2.itc.cn\/images01\/20211009\/efa1b962cea4400eab63717cc9604b92.png\" alt=\"\"\/><\/figure>\n\n\n\n<p class=\"has-text-align-left\">     \u7ed3\u5408\u4e86NeRF\u548cMultiplane Image\uff08MPI\uff09\uff0c\u63d0\u51fa\u4e86\u4e00\u79cd\u65b0\u7684\u4e09\u7ef4\u7a7a\u95f4\u8868\u8fbe\u65b9\u5f0fMINE\u3002MINE\u5229\u7528\u4e86NeRF\u7684\u601d\u8def\uff0c\u5c06MPI\u6269\u5c55\u6210\u4e86\u8fde\u7eed\u6df1\u5ea6\u7684\u5f62\u5f0f\u3002\u8f93\u5165\u5355\u5f20RGB\u56fe\u7247\uff0c\u6211\u4eec\u7684\u65b9\u6cd5\u4f1a\u5bf9source\u76f8\u673a\u7684\u89c6\u9525\uff08frustum\uff09\u505a\u7a20\u5bc6\u7684\u4e09\u7ef4\u91cd\u5efa\uff0c\u540c\u65f6\u5bf9\u88ab\u906e\u6321\u7684\u90e8\u5206\u505ainpainting\uff0c\u9884\u6d4b\u51fa\u76f8\u673a\u89c6\u9525\u7684\u4e09\u7ef4\u8868\u8fbe\u3002\u5229\u7528\u8fd9\u4e2a\u4e09\u7ef4\u8868\u8fbe\uff0c\u7ed9\u51fatarget\u76f8\u673a\u76f8\u5bf9\u4e8esource\u76f8\u673a\u7684\u5728\u4e09\u7ef4\u7a7a\u95f4\u4e2d\u7684\u76f8\u5bf9\u4f4d\u7f6e\u548c\u89d2\u5ea6\u53d8\u5316\uff08rotation and translation\uff09\uff0c\u6211\u4eec\u53ef\u4ee5\u65b9\u4fbf\u4e14\u9ad8\u6548\u5730\u6e32\u67d3\u51fa\u5728\u76ee\u6807\u76f8\u673a\u89c6\u56fe\u4e0b\u7684RGB\u56fe\u7247\u4ee5\u53ca\u6df1\u5ea6\u56fe\u3002<\/p>\n\n\n\n<p>       MINE\u5728KITTI\uff0cRealEstate10K\u4ee5\u53caFlowers Light Fields\u6570\u636e\u96c6\u4e0a\uff0c\u751f\u6210\u8d28\u91cf\u5927\u5e45\u8d85\u8fc7\u4e86\u5f53\u524d\u5355\u89c6\u56fe\u5408\u6210\u7684state-of-the-art\u3002\u540c\u65f6\uff0c\u5728\u6df1\u5ea6\u4f30\u8ba1benchmark iBims-1\u548cNYU-v2\u4e0a\uff0c\u867d\u7136\u6211\u4eec\u5728\u8bad\u7ec3\u4e2d\u53ea\u4f7f\u7528\u4e86RGB\u56fe\u7247\u548csparse\u6df1\u5ea6\u76d1\u7763\uff0cMINE\u5728\u5355\u76ee\u6df1\u5ea6\u4f30\u8ba1\u4efb\u52a1\u4e0a\u53d6\u5f97\u4e86\u975e\u5e38\u63a5\u8fd1\u5168\u76d1\u7763state-of-the-art\u7684performance\uff0c\u5e76\u5927\u5e45\u8d85\u8d8a\u4e86\u5176\u4ed6\u5f31\u76d1\u7763\u7684\u65b9\u6cd5\u3002<\/p>\n\n\n\n<p>Introduction and Related Works<\/p>\n\n\n\n<p>\u89c6\u56fe\u5408\u6210\uff08novel view synthesis\uff09\u9700\u8981\u89e3\u51b3\u7684\u95ee\u9898\u662f\uff1a\u5728\u4e00\u4e2a\u573a\u666f\uff08scene\uff09\u4e0b\uff0c\u8f93\u5165\u4e00\u4e2a\u6216\u591a\u4e2a\u56fe\u7247\uff0c\u5b83\u4eec\u5404\u81ea\u7684\u76f8\u673a\u5185\u53c2\u548c\u5916\u53c2\uff08source camera pose\uff09\uff0c\u4e4b\u540e\u5bf9\u4e8e\u4efb\u610f\u7684\u76f8\u673a\u4f4d\u7f6e\u548c\u89d2\u5ea6\uff08target camera pose\uff09\uff0c\u6211\u4eec\u60f3\u8981\u751f\u6210\u573a\u666f\u5728\u8be5\u76f8\u673a\u89c6\u56fe\u4e0b\u7684RGB\u56fe\u7247\u3002\u8981\u89e3\u51b3\u8fd9\u4e2a\u95ee\u9898\uff0c\u6211\u4eec\u7684\u6a21\u578b\u9700\u8981\u5b66\u4f1a\u573a\u666f\u7684\u51e0\u4f55\u7ed3\u6784\uff0c\u540c\u65f6\u5bf9\u88ab\u906e\u6321\u7684\u90e8\u5206\u505ainpainting\u3002\u5b66\u672f\u754c\u8bbe\u8ba1\u4e86\u5f88\u591a\u5229\u7528learning\u7684\u65b9\u6cd5\u9884\u6d4b\u573a\u666f\u76843D\/2.5D\u8868\u8fbe\uff0c\u5176\u4e2d\u8ddf\u6211\u4eec\u8f83\u76f8\u5173\u7684\u662fMPI\uff08Multiplane Image\uff09[1, 2, 3]\u3002MPI\u5305\u542b\u4e86\u591a\u4e2a\u5e73\u9762\u7684&nbsp;RGB-\u03b1\u56fe\u7247\uff0c\u5176\u4e2d\u6bcf\u4e2a\u5e73\u9762\u8868\u8fbe\u573a\u666f\u5728\u67d0\u4e2a\u6df1\u5ea6\u4e2d\u7684\u5185\u5bb9\uff0c\u5b83\u7684\u4e3b\u8981\u7f3a\u70b9\u5728\u4e8e\u6df1\u5ea6\u662f\u56fa\u5b9a\u53ca\u79bb\u6563\u7684\uff0c\u8fd9\u4e2a\u7f3a\u70b9\u9650\u5236\u4e86\u5b83\u5bf9\u4e09\u7ef4\u7a7a\u95f4\u7684\u8868\u8fbe\u80fd\u529b\u3002<\/p>\n\n\n\n<p>\u8fd1\u5e74\u6765\uff0c\u8fd9\u4e2a\u9886\u57df\u7684\u5f53\u7ea2\u70b8\u5b50\u9e21\u65e0\u7591\u662fECCV 2020\u7684NeRF [5]\u3002\u4e0e\u4f20\u7edf\u7684\u4e00\u4e9b\u624b\u5de5\u8bbe\u8ba1\u7684\u663e\u5f0f\u4e09\u7ef4\u8868\u8fbe\uff08Light Fields\uff0cLDI\uff0cMPI\u7b49\uff09\u4e0d\u540c\uff0cNeRF\u628a\u6574\u4e2a\u4e09\u7ef4\u7a7a\u95f4\u7684\u51e0\u4f55\u4fe1\u606f\u4e0etexture\u4fe1\u606f\u5168\u90e8\u7528\u4e00\u4e2aMLP\u7684\u6743\u91cd\u6765\u8868\u8fbe\uff0c\u8f93\u5165\u4efb\u610f\u4e00\u4e2a\u7a7a\u95f4\u5750\u6807\u4ee5\u53ca\u89c2\u5bdf\u89d2\u5ea6\uff0cMLP\u4f1a\u9884\u6d4b\u4e00\u4e2aRGB\u503c\u548cvolume density\u3002\u76ee\u6807\u56fe\u7247\u7684\u6e32\u67d3\u901a\u8fc7ray tracing\u548cvolume rendering\u7684\u65b9\u5f0f\u6765\u5b8c\u6210\u3002\u5c3d\u7ba1NeRF\u7684\u6548\u679c\u975e\u5e38\u60ca\u8273\uff0c\u4f46\u5b83\u7684\u7f3a\u70b9\u4e5f\u975e\u5e38\u660e\u663e\uff1a1. \u4e00\u4e2a\u6a21\u578b\u53ea\u80fd\u8868\u8fbe\u4e00\u4e2a\u573a\u666f\uff0c\u4e14\u4f18\u5316\u4e00\u4e2a\u573a\u666f\u8017\u65f6\u4e45\uff1b2. per-pixel\u6e32\u67d3\u8f83\u4e3a\u4f4e\u6548\uff1b3. \u6cdb\u5316\u80fd\u529b\u8f83\u5dee\uff0c\u4e00\u4e2a\u573a\u666f\u9700\u8981\u8f83\u591a\u7684\u7167\u7247\u624d\u80fd\u8bad\u7ec3\u597d\u3002<\/p>\n\n\n\n<p><strong>\u65b9\u6cd5\u7efc\u8ff0<\/strong><\/p>\n\n\n\n<p>\u8be5\u56e2\u961f\u91c7\u7528\u4e00\u4e2a encoder-decoder \u7684\u7ed3\u6784\u6765\u751f\u6210\u4e09\u7ef4\u8868\u8fbe\uff1a<\/p>\n\n\n\n<ol><li>Encoder \u662f\u4e00\u4e2a\u5168\u5377\u79ef\u7f51\u7edc\uff0c\u8f93\u5165\u4e3a\u5355\u4e2a RGB \u56fe\u7247\uff0c\u8f93\u51fa\u4e3a feature maps\uff1b<\/li><li>Decoder \u4e5f\u662f\u4e00\u4e2a\u5168\u5377\u79ef\u7f51\u7edc\uff0c\u8f93\u5165\u4e3a encoder \u8f93\u51fa\u7684 feature map\uff0c\u4ee5\u53ca\u4efb\u610f\u6df1\u5ea6\u503c\uff08repeat + concat\uff09\uff0c\u8f93\u51fa\u8be5\u6df1\u5ea6\u4e0b\u7684 RGB-sigma \u56fe\u7247\uff1b<\/li><li>\u6700\u7ec8\u7684\u4e09\u7ef4\u8868\u8fbe\u7531\u591a\u4e2a\u5e73\u9762\u7ec4\u6210\uff0c\u4e5f\u5c31\u662f\u8bf4\u5728\u4e00\u6b21\u5b8c\u6574\u7684 forward \u4e2d\uff0cencoder \u9700\u8981 inference \u4e00\u6b21\uff0c\u800c decoder \u9700\u8981 inference N \u6b21\u83b7\u5f97\u4e2a N \u5e73\u9762\u3002<\/li><\/ol>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p4.itc.cn\/images01\/20211009\/d93cdbf54e134352986b970ec002419f.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>\u83b7\u5f97\u4e09\u7ef4\u8868\u8fbe\u540e\uff0c\u4e0d\u518d\u9700\u8981\u4efb\u4f55\u7684\u7f51\u7edc inference\uff0c\u6e32\u67d3\u4efb\u610f target \u76f8\u673a pose \u4e0b\u7684\u89c6\u89d2\u53ea\u9700\u8981\u4e24\u6b65\uff1a<\/p>\n\n\n\n<ol><li>\u5229\u7528 homography wrapping \u5efa\u7acb\u50cf\u7d20\u70b9\u95f4\u7684 correspondence\u3002\u53ef\u4ee5\u60f3\u8c61\uff0c\u4ece target \u76f8\u673a\u5c04\u51fa\u4e00\u6761\u5149\u7ebf\uff0c\u8fd9\u6761\u5149\u7ebf\u4e0e target \u56fe\u7247\u7684\u4e00\u4e2a\u50cf\u7d20\u70b9\u76f8\u4ea4\uff0c\u7136\u540e\uff0c\u7814\u7a76\u8005\u5ef6\u957f\u8fd9\u6761\u5c04\u7ebf\uff0c\u8ba9\u5b83\u4e0e source \u76f8\u673a\u89c6\u9525\u7684\u5404\u4e2a\u5e73\u9762\u76f8\u4ea4\u3002\u76f8\u4ea4\u70b9\u7684 RGB-sigma \u503c\u53ef\u4ee5\u901a\u8fc7 bilinear sampling \u83b7\u5f97\uff1b<\/li><li>\u5229\u7528 volume rendering \u5c06\u5149\u7ebf\u4e0a\u7684\u70b9\u6e32\u67d3\u5230\u76ee\u6807\u56fe\u7247\u50cf\u7d20\u70b9\u4e0a\uff0c\u83b7\u5f97\u8be5\u50cf\u7d20\u70b9\u7684 RGB \u503c\u4e0e\u6df1\u5ea6\u3002<\/li><\/ol>\n\n\n\n<h4>\u4e09\u7ef4\u8868\u8fbe\u4e0e\u6e32\u67d3<\/h4>\n\n\n\n<p><strong>1. Planar Neural Radiance Field<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" width=\"966\" height=\"537\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-55.png\" alt=\"\" class=\"wp-image-11989\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-55.png 966w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-55-300x167.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-55-768x427.png 768w\" sizes=\"(max-width: 966px) 100vw, 966px\" \/><\/figure>\n\n\n\n<p><strong>2. Rendering Process<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" width=\"971\" height=\"573\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-56.png\" alt=\"\" class=\"wp-image-11991\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-56.png 971w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-56-300x177.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-56-768x453.png 768w\" sizes=\"(max-width: 971px) 100vw, 971px\" \/><\/figure>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" width=\"943\" height=\"532\" src=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-57.png\" alt=\"\" class=\"wp-image-11992\" srcset=\"http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-57.png 943w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-57-300x169.png 300w, http:\/\/139.9.1.231\/wp-content\/uploads\/2023\/01\/image-57-768x433.png 768w\" sizes=\"(max-width: 943px) 100vw, 943px\" \/><\/figure>\n\n\n\n<p>\u5b8c\u6210\u8fd9\u4e24\u6b65\u4e4b\u540e\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u901a\u8fc7\u4e0a\u9762volume rendering\u7684\u516c\u5f0f\u6e32\u67d3\u4efb\u610ftarget camera\u4e0b\u7684\u89c6\u56fe\u4e86\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c<strong><em>\u5728\u83b7\u5f973D\u8868\u8fbe\u540e\uff0c\u6e32\u67d3\u4efb\u610ftarget camera pose\u4e0b\u7684\u89c6\u56fe\u90fd\u53ea\u9700\u8981\u8fd9\u4e24\u4e2a\u6b65\u9aa4\uff0c\u65e0\u9700\u518d\u505a\u989d\u5916\u7684\u7f51\u7edcinference<\/em><\/strong>\u3002<\/p>\n\n\n\n<p><strong>Scale \u6821\u6b63<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img src=\"https:\/\/p0.itc.cn\/images01\/20211009\/bad781820ffb49c5972a6a924eb8433b.png\" alt=\"\"\/><\/figure>\n\n\n\n<p>MINE \u53ef\u4ee5\u5229\u7528 structure-from-motion \u8ba1\u7b97\u7684\u76f8\u673a\u53c2\u6570\u4e0e\u70b9\u4e91\u8fdb\u884c\u573a\u666f\u7684\u5b66\u4e60\uff0c\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6df1\u5ea6\u662f ambiguous \u7684\u3002\u7531\u4e8e\u5728\u8fd9\u4e2a\u65b9\u6cd5\u4e2d\uff0c\u6df1\u5ea6\u91c7\u6837\u7684\u8303\u56f4\u662f\u56fa\u5b9a\u7684\u3002\u6240\u4ee5\u9700\u8981\u8ba1\u7b97\u4e00\u4e2a scale factor\uff0c\u4f7f\u7f51\u7edc\u9884\u6d4b\u7684 scale \u4e0e structure-from-motion \u7684 scale \u8fdb\u884c\u5bf9\u9f50\u3002\u56e2\u961f\u5229\u7528\u901a\u8fc7 Structure from Motion \u83b7\u5f97\u7684\u6bcf\u4e2a\u56fe\u7247\u7684\u53ef\u89c1 3D \u70b9 P \u4ee5\u53ca\u7f51\u7edc\u9884\u6d4b\u7684\u6df1\u5ea6\u56fe Z \u8ba1\u7b97 scale factor\uff1a<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><img loading=\"lazy\" src=\"https:\/\/p7.itc.cn\/images01\/20211009\/e107dd1e5e8b43579dfa59614be91d3c.png\" alt=\"\" width=\"448\" height=\"64\"\/><\/figure><\/div>\n\n\n\n<p>\u83b7\u5f97 scale factor \u540e\uff0c\u5bf9\u76f8\u673a\u7684\u4f4d\u79fb\u8fdb\u884c scale\uff1a<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><img loading=\"lazy\" src=\"https:\/\/p4.itc.cn\/images01\/20211009\/caa4e692b87e425a8b332fbbbe5dfd3e.png\" alt=\"\" width=\"-115\" height=\"-26\"\/><\/figure><\/div>\n\n\n\n<p>\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u7531\u4e8e\u9700\u8981\u548c ground truth \u6bd4\u8f83\uff0c\u6240\u4ee5\u5728\u8bad\u7ec3\u548c\u6d4b\u8bd5\u65f6\u9700\u8981\u505a scale calibration\u3002\u800c\u5728\u90e8\u7f72\u65f6\u4e0d\u9700\u8981\u505a\u8fd9\u4e00\u6b65\u3002<\/p>\n\n\n\n<p><strong>\u7aef\u5230\u7aef\u7684\u8bad\u7ec3<\/strong><\/p>\n\n\n\n<p>MINE \u53ef\u4ee5\u4ec5\u901a\u8fc7 RGB \u56fe\u7247\u5b66\u4e60\u5230\u573a\u666f\u7684\u4e09\u7ef4\u51e0\u4f55\u4fe1\u606f\uff0c\u8bad\u7ec3 Loss \u4e3b\u8981\u7531\u4e24\u90e8\u5206\u7ec4\u6210\uff1a<\/p>\n\n\n\n<p>1.Reconsturction loss\u2014\u2014\u8ba1\u7b97\u6e32\u67d3\u51fa\u7684 target \u56fe\u7247\u4e0e ground truth \u7684\u5dee\u5f02\uff1a<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><img loading=\"lazy\" src=\"https:\/\/p1.itc.cn\/images01\/20211009\/e67f0be6d2724c0ea63ef56e81927dbe.png\" alt=\"\" width=\"538\" height=\"43\"\/><\/figure><\/div>\n\n\n\n<p>2.Edge-aware smoothness loss\u2014\u2014\u786e\u4fdd\u5728\u56fe\u7247\u989c\u8272\u6ca1\u6709\u7a81\u53d8\u7684\u5730\u65b9\uff0c\u6df1\u5ea6\u4e5f\u4e0d\u4f1a\u7a81\u53d8\uff0c\u8fd9\u91cc\u4e3b\u8981\u53c2\u8003\u4e86 monodepth2 [6] \u79cd\u7684\u5b9e\u73b0\uff1a<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><img loading=\"lazy\" src=\"https:\/\/p8.itc.cn\/images01\/20211009\/36cc038d5f3a4d0492b1f1f5608d1df0.png\" alt=\"\" width=\"573\" height=\"36\"\/><\/figure><\/div>\n\n\n\n<p>3.Sparse disparity loss\u2014\u2014\u5728\u8bad\u7ec3\u96c6\u5404\u573a\u666f\u7684 scale \u4e0d\u4e00\u6837\u65f6\uff0c\u5229\u7528 structure-from-motion \u83b7\u5f97\u7684\u7a00\u758f\u70b9\u4e91\u8f85\u52a9\u573a\u666f\u51e0\u4f55\u4fe1\u606f\u7684\u5b66\u4e60\uff1a<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><img loading=\"lazy\" src=\"https:\/\/p3.itc.cn\/images01\/20211009\/ad8dd6e9ac3044dd88e11105c3798fee.png\" alt=\"\" width=\"392\" height=\"137\"\/><\/figure><\/div>\n\n\n\n<p><strong>MINE \u4e0e MPI\u3001NeRF \u7684\u6bd4\u8f83<\/strong><\/p>\n\n\n\n<p>MINE \u662f MPI \u7684\u4e00\u79cd\u8fde\u7eed\u6df1\u5ea6\u7684\u6269\u5c55\uff0c\u76f8\u6bd4\u4e8e MPI \u548c NeRF\uff0cMINE \u6709\u51e0\u4e2a\u660e\u663e\u7684\u4f18\u52bf\uff1a<\/p>\n\n\n\n<ol><li>\u4e0e NeRF \u76f8\u6bd4\uff0cMINE \u80fd\u591f\u6cdb\u5316\u5230\u8bad\u7ec3\u96c6\u6ca1\u6709\u51fa\u73b0\u8fc7\u7684\u573a\u666f\uff1b<\/li><li>\u4e0e NeRF \u7684\u9010\u70b9\u6e32\u67d3\u76f8\u6bd4\uff0cMINE \u7684\u6e32\u67d3\u975e\u5e38\u9ad8\u6548\uff1b<\/li><li>\u4e0e MPI \u76f8\u6bd4\uff0cMINE \u7684\u6df1\u5ea6\u662f\u8fde\u7eed\u7684\uff0c\u80fd\u7a20\u5bc6\u5730\u8868\u793a\u76f8\u673a\u7684\u89c6\u9525\uff1b<\/li><li>MPI \u901a\u8fc7 alpha \u5408\u6210\uff08alpha compositing\uff09\u8fdb\u884c\u6e32\u67d3\uff0c\u4f46\u8be5\u65b9\u6cd5\u4e0e\u5c04\u7ebf\u4e0a\u70b9\u4e4b\u95f4\u7684\u8ddd\u79bb\u65e0\u5173\uff0c\u800c MINE \u5229\u7528 volume rendering \u89e3\u51b3\u4e86\u8fd9\u4e2a\u9650\u5236\u3002<\/li><\/ol>\n\n\n\n<p>\u7136\u800c\uff0cMINE \u4e5f\u6709\u4e00\u4e9b\u81ea\u8eab\u7684\u5c40\u9650\u6027\uff1a<\/p>\n\n\n\n<ol><li><strong>\u7531\u4e8e\u8f93\u5165\u662f\u5355\u5f20\u56fe\u7247\uff0cMINE \u65e0\u6cd5\u8868\u8fbe\u76f8\u673a\u89c6\u9525\u4ee5\u5916\u7684\u4e09\u7ef4\u7a7a\u95f4\uff1b<\/strong><\/li><li><strong>\u7531\u4e8e MINE \u7684\u8f93\u5165\u91cc\u6ca1\u6709\u89c2\u5bdf\u89d2\u5ea6\uff0c\u6240\u4ee5\u5176\u65e0\u6cd5\u5bf9\u4e00\u4e9b\u590d\u6742\u7684 view-dependent \u6548\u679c\uff08\u5982\u5149\u76d8\u4e0a\u7684\u5f69\u8679\u7b49\uff09\u8fdb\u884c\u5efa\u6a21\u3002<\/strong><\/li><\/ol>\n\n\n\n<p>[1]. Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, Noah Snavely. Stereo Magnification: Learning View Synthesis using Multiplane Images. (SIGGRAPH 2018)<\/p>\n\n\n\n<p>[2]. Ben Mildenhall, Pratul P. Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, Abhishek Kar. Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines. (SIGGRAPH 2019)<\/p>\n\n\n\n<p>[3]. Richard Tucker, Noah Snavely. Single-View View Synthesis with Multiplane Images. (CVPR 2020)<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7aef\u5230\u7aef\u7c7b\u578b \u7528MPI\uff08Multi-Plane Image \uff09\u4ee3\u66ffNeRF\u7684RGB\u03c3\u4f5c\u4e3a\u7f51\u7edc\u7684\u8f93\u51fa \u6765\u81ea\u5b57\u8282\u8df3\u52a8 &hellip; <a href=\"http:\/\/139.9.1.231\/index.php\/2023\/01\/07\/mine\/\" class=\"more-link\">\u7ee7\u7eed\u9605\u8bfb<span class=\"screen-reader-text\">MINE&#8211;\u5229\u7528\u5355\u5f20\u56fe\u7247\u505a\u4e09\u7ef4\u91cd\u5efa<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[35,31,9],"tags":[],"_links":{"self":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/11485"}],"collection":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/comments?post=11485"}],"version-history":[{"count":36,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/11485\/revisions"}],"predecessor-version":[{"id":12496,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/11485\/revisions\/12496"}],"wp:attachment":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/media?parent=11485"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/categories?post=11485"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/tags?post=11485"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}