{"id":7449,"date":"2026-01-19T21:10:34","date_gmt":"2026-01-19T13:10:34","guid":{"rendered":"https:\/\/infernews.com\/?p=7449"},"modified":"2026-01-19T22:48:39","modified_gmt":"2026-01-19T14:48:39","slug":"shaper-%e9%9a%a8%e6%8b%8d%e5%8f%af%e9%82%84%e5%8e%9f-3d-%e5%a0%b4%e6%99%af","status":"publish","type":"post","link":"https:\/\/infernews.com\/blog\/shaper-%e9%9a%a8%e6%8b%8d%e5%8f%af%e9%82%84%e5%8e%9f-3d-%e5%a0%b4%e6%99%af\/","title":{"rendered":"ShapeR \u96a8\u62cd\u53ef\u9084\u539f 3D \u5834\u666f"},"content":{"rendered":"\n<p><a href=\"https:\/\/facebookresearch.github.io\/ShapeR\/\" target=\"_blank\" rel=\"noreferrer noopener\">ShapeR<\/a> \u662f\u4ee5 <a href=\"https:\/\/infernews.com\/rectified-flow\/\">rectified\u2011flow<\/a> \u70ba\u57fa\u790e\u7684\u751f\u6210\u6a21\u578b\uff0c\u80fd\u76f4\u63a5\u5f9e\u65e5\u5e38\u62cd\u651d\u7684\u5f71\u50cf\u5e8f\u5217\uff08\u5373\u300c\u4e0d\u898f\u5247\u300d\u6355\u6349\uff09\u91cd\u5efa\u9ad8\u4fdd\u771f\u7684\u4e09\u7dad\u7269\u4ef6\u3002\u6574\u9ad4\u6d41\u7a0b\u5927\u81f4\u53ef\u4ee5\u5206\u6210\u5e7e\u500b\u6b65\u9a5f\uff1a<\/p>\n\n\n\n<p>\u5148\u7528\u73fe\u6210\u7684\u8996\u89ba\u2011\u6163\u6027 SLAM \u6f14\u7b97\u6cd5\u628a\u93e1\u982d\u79fb\u52d5\u548c\u7a00\u758f\u9ede\u96f2\u62ff\u51fa\u4f86\uff0c\u63a5\u8457\u518d\u4ea4\u7d66 3D \u7269\u4ef6\u5075\u6e2c\u5668\u628a\u6bcf\u500b\u76ee\u6a19\u7269\u5206\u5272\u51fa\u4f86\u3002\u6bcf\u500b\u5075\u6e2c\u5230\u7684\u7269\u4ef6\u6703\u5f97\u5230\u5e7e\u5f35\u5177\u5099\u76f8\u6a5f\u4f4d\u59ff\u7684\u591a\u8996\u89d2\u5716\u7247\u3001\u4e00\u7d44\u7a00\u758f\u7684 SLAM \u9ede\uff0c\u9084\u6709\u4e00\u6bb5\u7531\u8996\u89ba\u8a9e\u8a00\u6a21\u578b\u81ea\u52d5\u7522\u751f\u7684\u6587\u5b57\u8aaa\u660e\u3002\u9019\u4e9b\u8cc7\u8a0a\uff08\u9ede\u96f2\u3001\u591a\u8996\u5716\u3001\u6587\u5b57\uff09\u6703\u88ab\u5c01\u88dd\u6210\u4e00\u500b\u591a\u6a21\u6001\u7684\u689d\u4ef6\u5411\u91cf\uff0c\u9001\u7d66\u8a13\u7df4\u597d\u7684 rectified\u2011flow Transformer \u53bb\u53bb\u566a\u3002<\/p>\n\n\n\n<p>Transfomer \u8f38\u51fa\u7684 latent VecSet \u63a5\u8457\u7d93\u904e\u4e00\u500b 3D VAE \u89e3\u78bc\uff0c\u6700\u5f8c\u751f\u6210\u5b8c\u6574\u7684\u4e09\u7dad\u7db2\u683c\u3002\u6574\u500b\u6a21\u578b\u53ea\u9700\u8981\u5728\u5408\u6210\u8cc7\u6599\u4e0a\u5148\u505a\u5927\u91cf\u7684\u55ae\u7269\u4ef6\u9810\u8a13\u7df4\uff0c\u63a5\u8457\u518d\u5728\u66f4\u5177\u6311\u6230\u6027\u7684\u5408\u6210\u5834\u666f\u8207\u771f\u5be6\u5834\u666f\u8cc7\u6599\u4e0a\u9032\u884c\u5169\u968e\u6bb5\u7684\u8a13\u7df4\uff0c\u904e\u7a0b\u4e2d\u6703\u4e0d\u65b7\u52a0\u5165\u5404\u7a2e\u81ea\u7136\u7684\u80cc\u666f\u3001\u906e\u64cb\u3001\u566a\u8072\u4ee5\u53ca augmentations\uff0c\u8b93\u6a21\u578b\u5b78\u6703\u5728\u300c\u96dc\u4e82\u300d\u7684\u74b0\u5883\u4e0b\u4ecd\u4fdd\u6301\u7a69\u5b9a\u3002<\/p>\n\n\n\n<p>\u7814\u7a76\u5718\u968a\u4e5f\u91cb\u51fa\u4e86\u4e00\u500b\u5c08\u5c6c\u7684\u8a55\u4f30\u8cc7\u6599\u96c6\uff1a\u88e1\u9762\u6709 178 \u500b\u771f\u5be6\u4e16\u754c\u7684\u7269\u4ef6\u5206\u5e03\u5728\u4e03\u500b\u5834\u666f\u4e2d\uff0c\u914d\u6709\u5b8c\u6574\u7684\u5730\u9762\u771f\u503c\u7db2\u683c\u3001\u914d\u5c0d\u597d\u7684\u591a\u8996\u5716\u5f71\u50cf\u3001SLAM \u9ede\u96f2\u8207\u6587\u5b57\u63cf\u8ff0\u3002\u9019\u7b46\u8cc7\u6599\u5c08\u9580\u7528\u4f86\u6e2c\u8a66\u5728\u91ce\u5916\u6355\u6349\u6642\u7684\u906e\u64cb\u3001\u96dc\u4e82\u3001\u89e3\u6790\u5ea6\u8b8a\u5316\u7b49\u60c5\u6cc1\uff0c\u8b93\u6a21\u578b\u5728\u66f4\u8cbc\u8fd1\u5be6\u52d9\u7684\u689d\u4ef6\u4e0b\u63a5\u53d7\u6e2c\u8a66\u3002<\/p>\n\n\n\n<p>\u5728\u6e2c\u8a66\u7d50\u679c\u4e0a\uff0c<a href=\"https:\/\/facebookresearch.github.io\/ShapeR\/\" target=\"_blank\" rel=\"noreferrer noopener\">ShapeR<\/a> \u5728 Chamfer Distance \u6307\u6a19\u4e0a\u6bd4\u76ee\u524d\u6700\u597d\u7684\u65b9\u6cd5\u63d0\u5347\u4e86 2.7 \u500d\uff0c\u986f\u793a\u51fa\u5728\u300c\u4e0d\u898f\u5247\u300d\u60c5\u5883\u4e0b\u7684\u7a69\u5b9a\u6027\u78ba\u5be6\u6bd4\u5148\u524d\u7684\u55ae\u8996\u5716\u6216\u5168\u5c40\u5834\u666f\u91cd\u5efa\u65b9\u5f0f\u66f4\u4f73\u3002\u76f8\u8f03\u65bc\u540c\u6a23\u6d41\u884c\u7684 <a href=\"https:\/\/ai.meta.com\/sam3d\/\" target=\"_blank\" rel=\"noreferrer noopener\">SAM3D<\/a> \u65b9\u6cd5\uff0cShapeR \u7684\u7279\u8272\u5728\u65bc\u5b83\u5229\u7528\u591a\u8996\u5716\u7684\u5e7e\u4f55\u8cc7\u8a0a\uff08SLAM \u9ede\u3001\u76f8\u6a5f\u4f4d\u59ff\uff09\u4f86\u4fdd\u8b49\u5f62\u72c0\u7684\u5c3a\u5ea6\u8207\u771f\u5be6\u611f\uff0c\u800c SAM3D \u5247\u4f9d\u8cf4\u55ae\u5f35\u5716\u50cf\u8207\u4e92\u52d5\uff0c\u5c0d\u65bc\u898f\u6a21\u548c\u8996\u89d2\u7684\u4e00\u81f4\u6027\u8f03\u5f31\u3002\u5169\u8005\u5176\u5be6\u53ef\u4ee5\u4e92\u88dc\u2014\u2014\u628a ShapeR \u7684\u5e7e\u4f55\u7d50\u679c\u518d\u9001\u7d66 SAM3D \u751f\u6210\u66f4\u8c50\u5bcc\u7684\u6750\u8cea\u6216\u7d30\u7bc0\u3002<\/p>\n\n\n\n<p>\u7e3d\u7d50\u4f86\u8aaa\uff0cShapeR \u900f\u904e\u628a SLAM \u9ede\u96f2\u30013D \u5075\u6e2c\u3001\u591a\u8996\u5716\u5f71\u50cf\u548c\u81ea\u52d5\u6587\u5b57\u8aaa\u660e\u9019\u5e7e\u7a2e\u8cc7\u8a0a\u5168\u90e8\u7d50\u5408\u8d77\u4f86\uff0c\u505a\u51fa\u4e00\u500b\u80fd\u5728\u65e5\u5e38\u62cd\u651d\u5834\u666f\u4e0b\u7522\u751f\u9ad8\u54c1\u8cea\u3001\u5177\u5099\u5ea6\u91cf\u771f\u5be6\u6027\u7684\u55ae\u7269\u4ef6\u4e09\u7dad\u5f62\u72c0\u7684\u751f\u6210\u6a21\u578b\uff0c\u4e26\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u6e2c\u8a66\u7d20\u6750\u8207\u6a21\u578b\u8cc7\u6e90\u8b93\u7814\u7a76\u8005\u76f4\u63a5\u4f7f\u7528\u3002<\/p>\n\n\n<figure class=\"wp-block-embed-youtube wp-block-embed is-type-video is-provider-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio\"><div class=\"lyte-wrapper\" title=\"ShapeR: Robust Conditional 3D Shape Generation from Casual Captures\" style=\"width:853px;max-width:100%;margin:5px auto;\"><div class=\"lyMe\" id=\"WYL_EbY30KAA55I\" itemprop=\"video\" itemscope itemtype=\"https:\/\/schema.org\/VideoObject\"><div><meta itemprop=\"thumbnailUrl\" content=\"https:\/\/infernews.com\/blog\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FEbY30KAA55I%2Fhqdefault.jpg\" \/><meta itemprop=\"embedURL\" content=\"https:\/\/www.youtube.com\/embed\/EbY30KAA55I\" \/><meta itemprop=\"duration\" content=\"PT4M28S\" \/><meta itemprop=\"uploadDate\" content=\"2026-01-19T11:16:37Z\" \/><\/div><div id=\"lyte_EbY30KAA55I\" data-src=\"https:\/\/infernews.com\/blog\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FEbY30KAA55I%2Fhqdefault.jpg\" class=\"pL\"><div class=\"tC\"><div class=\"tT\" itemprop=\"name\">ShapeR: Robust Conditional 3D Shape Generation from Casual Captures<\/div><\/div><div class=\"play\"><\/div><div class=\"ctrl\"><div class=\"Lctrl\"><\/div><div class=\"Rctrl\"><\/div><\/div><\/div><noscript><a href=\"https:\/\/youtu.be\/EbY30KAA55I\" rel=\"nofollow\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/infernews.com\/blog\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FEbY30KAA55I%2F0.jpg\" alt=\"ShapeR: Robust Conditional 3D Shape Generation from Casual Captures\" width=\"853\" height=\"460\" \/><br \/>Watch this video on YouTube<\/a><\/noscript><meta itemprop=\"description\" content=\"ShapeR performs generative, object-centric 3D reconstruction from image sequences by leveraging multimodal inputs and robust training strategies. For more details, check out the project here.\"><\/div><\/div><div class=\"lL\" style=\"max-width:100%;width:853px;margin:5px auto;\"><\/div><figcaption><\/figcaption><\/figure>\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th class=\"has-text-align-left\" data-align=\"left\">\u9762\u5411<\/th><th class=\"has-text-align-left\" data-align=\"left\"><a href=\"https:\/\/facebookresearch.github.io\/ShapeR\/\">ShapeR<\/a><\/th><th class=\"has-text-align-left\" data-align=\"left\"> <a href=\"https:\/\/ai.meta.com\/sam3d\/\" target=\"_blank\" rel=\"noreferrer noopener\">SAM3D<\/a><\/th><\/tr><\/thead><tbody><tr><td class=\"has-text-align-left\" data-align=\"left\">\u8f38\u5165<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u591a\u8996\u89d2\u5e8f\u5217 + SLAM \u9ede + caption \u7b49\u591a\u6a21\u614b<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u55ae\u5f35\u5f71\u50cf +\uff08\u7269\u4ef6\u6642\u591a\u534a\u8981 mask \/ \u4e92\u52d5)<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\">\u4efb\u52d9\u91cd\u9ede<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u5834\u666f\u7d1a\u3001\u7269\u4ef6\u70ba\u4e2d\u5fc3\u7684<strong>\u5ea6\u91cf\u91cd\u5efa<\/strong>\u8207\u4f48\u5c40<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u55ae\u8996\u5716<strong>\u9ad8\u54c1\u8cea\u5e7e\u4f55 + \u8cbc\u5716<\/strong>\u7684\u7269\u9ad4\/\u4eba\u9ad4\u91cd\u5efa\u200b<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\">\u5e7e\u4f55\u7cbe\u5ea6<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u5f37\u8abf metric accuracy\u3001\u76f8\u5c0d\u5c3a\u5ea6\u8207\u4f48\u5c40\u4e00\u81f4\u6027<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u53ef\u7f3a\u4e4f\u7cbe\u78ba\u6bd4\u4f8b\u8207 layout\uff0c\u7279\u5225\u662f\u8907\u96dc\u5834\u666f\u200b<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\">\u7d0b\u7406 \/ \u5916\u89c0<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u8f03\u504f\u5e7e\u4f55\u8207\u5834\u666f\u7d50\u69cb\uff08\u5b98\u7db2\u91cd\u9ede\u5728 shape\uff09\u200b<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u5f37\u8abf photoreal \u7d0b\u7406\u8207\u771f\u5be6\u5916\u89c0 priors<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\">\u4e92\u52d5\u9700\u6c42<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u4e0d\u9700\u8981\u4f7f\u7528\u8005\u4e92\u52d5\uff0cpipeline \u81ea\u52d5\u8655\u7406<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u9700\u8981\u7269\u4ef6 mask \/ prompt\uff0c\u5c6c\u65bc promptable \/ interactive workflow\u200b<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\">\u8a13\u7df4\u6578\u64da<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u5408\u6210\u591a\u6a21\u614b\u5834\u666f\uff08SLAM + \u591a\u8996\u5716\uff09<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u5927\u898f\u6a21\u771f\u5be6 image\u21923D\uff08Objects\/Body \u5404\u81ea\u7684 dataset\uff09<\/td><\/tr><tr><td class=\"has-text-align-left\" data-align=\"left\">\u9069\u5408\u5834\u666f<\/td><td class=\"has-text-align-left\" data-align=\"left\">AR \u773c\u93e1 \/ \u6a5f\u5668\u4eba\u591a\u8996\u89d2\u611f\u77e5\u3001\u5834\u666f mapping\u3001\u5b78\u8853\u8a55\u6e2c<\/td><td class=\"has-text-align-left\" data-align=\"left\">\u5546\u696d\u61c9\u7528\uff1a\u96fb\u5546 AR\u3001human pose &amp; shape\u3001\u55ae\u5716 3D content creation<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>ShapeR \u662f\u4ee5 rectified\u2011flow \u70ba\u57fa\u790e\u7684\u751f\u6210\u6a21\u578b\uff0c\u80fd\u76f4\u63a5\u5f9e\u65e5\u5e38\u62cd\u651d\u7684\u5f71\u50cf\u5e8f\u5217\uff08\u5373\u300c\u4e0d\u898f\u5247\u300d\u6355\u6349\uff09\u91cd\u5efa\u9ad8\u4fdd\u771f\u7684\u4e09\u7dad\u7269\u4ef6\u3002\u6574\u9ad4\u6d41\u7a0b\u5927\u81f4\u53ef\u4ee5\u5206\u6210\u5e7e\u500b\u6b65\u9a5f\uff1a \u5148\u7528\u73fe\u6210\u7684\u8996\u89ba\u2011\u6163\u6027 SLAM \u6f14\u7b97\u6cd5\u628a\u93e1\u982d\u79fb\u52d5\u548c\u7a00\u758f\u9ede\u96f2\u62ff\u51fa\u4f86\uff0c\u63a5\u8457\u518d\u4ea4\u7d66 3D \u7269\u4ef6\u5075\u6e2c\u5668\u628a\u6bcf\u500b\u76ee\u6a19\u7269\u5206\u5272\u51fa\u4f86\u3002\u6bcf\u500b\u5075\u6e2c\u5230\u7684\u7269\u4ef6\u6703\u5f97\u5230\u5e7e\u5f35\u5177\u5099\u76f8\u6a5f\u4f4d\u59ff\u7684\u591a\u8996\u89d2\u5716\u7247\u3001\u4e00\u7d44\u7a00\u758f\u7684 SLAM \u9ede\uff0c\u9084\u6709\u4e00\u6bb5\u7531\u8996\u89ba\u8a9e\u8a00\u6a21\u578b\u81ea\u52d5\u7522\u751f\u7684\u6587\u5b57\u8aaa\u660e\u3002\u9019\u4e9b\u8cc7\u8a0a\uff08\u9ede\u96f2\u3001\u591a\u8996\u5716\u3001\u6587\u5b57\uff09\u6703\u88ab\u5c01\u88dd\u6210\u4e00\u500b\u591a\u6a21\u6001\u7684\u689d\u4ef6\u5411\u91cf\uff0c\u9001\u7d66\u8a13\u7df4\u597d\u7684 rectified\u2011flow Transformer \u53bb\u53bb\u566a\u3002 Transfomer \u8f38\u51fa\u7684 latent VecSet \u63a5\u8457\u7d93\u904e\u4e00\u500b 3D VAE \u89e3\u78bc\uff0c\u6700\u5f8c\u751f\u6210\u5b8c\u6574\u7684\u4e09\u7dad\u7db2\u683c\u3002\u6574\u500b\u6a21\u578b\u53ea\u9700\u8981\u5728\u5408\u6210\u8cc7\u6599\u4e0a\u5148\u505a\u5927\u91cf\u7684\u55ae\u7269\u4ef6\u9810\u8a13\u7df4\uff0c\u63a5\u8457\u518d\u5728\u66f4\u5177\u6311\u6230\u6027\u7684\u5408\u6210\u5834\u666f\u8207\u771f\u5be6\u5834\u666f\u8cc7\u6599\u4e0a\u9032\u884c\u5169\u968e\u6bb5\u7684\u8a13\u7df4\uff0c\u904e\u7a0b\u4e2d\u6703\u4e0d\u65b7\u52a0\u5165\u5404\u7a2e\u81ea\u7136\u7684\u80cc\u666f\u3001\u906e\u64cb\u3001\u566a\u8072\u4ee5\u53ca augmentations\uff0c\u8b93\u6a21\u578b\u5b78\u6703\u5728\u300c\u96dc\u4e82\u300d\u7684\u74b0\u5883\u4e0b\u4ecd\u4fdd\u6301\u7a69\u5b9a\u3002 \u7814\u7a76\u5718\u968a\u4e5f\u91cb\u51fa\u4e86\u4e00\u500b\u5c08\u5c6c\u7684\u8a55\u4f30\u8cc7\u6599\u96c6\uff1a\u88e1\u9762\u6709 178 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