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\u8f66\u8def\u534f\u540c\u68c0\u6d4b\uff08Vehicle-to-Infrastructure\uff08V2I\uff09\uff09\u662f\u4e00\u79cd\u57fa\u4e8e\u667a\u80fd\u4ea4\u901a\u7cfb\u7edf\uff08ITS\uff09\u7684\u6280\u672f\uff0c\u65e8\u5728\u63d0\u9ad8\u4ea4\u901a\u5b89\u5168\u548c\u6548\u7387\u3002\u5b83\u5229\u7528\u8f66\u8f86\u548c\u9053\u8def\u57fa\u7840\u8bbe\u65bd\u4e4b\u95f4\u7684\u901a\u4fe1\uff0c\u5b9e\u73b0\u4ea4\u901a\u4fe1\u606f\u5171\u4eab\u548c\u534f\u540c\u884c\u9a76\u3002\u8fd1\u5e74\u6765\uff0c\u57fa\u4e8e\u5149\u63a2\u6d4b\u548c\u6d4b\u8ddd\uff08LiDAR\uff09\u70b9\u4e91\u7684\u4e09\u7ef4\u7269\u4f53\u68c0\u6d4b\u56e0\u5176\u5728\u667a\u80fd\u57ce\u5e02\u548c\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u5e7f\u6cdb\u5e94\u7528\u800c\u5907\u53d7\u5173\u6ce8\u3002\u7ea7\u8054\u6846\u67b6\u5728\u4e8c\u7ef4\u7269\u4f53\u68c0\u6d4b\u65b9\u9762\u663e\u793a\u51fa\u5176\u5148\u8fdb\u6027\uff0c\u4f46\u5728\u4e09\u7ef4\u7a7a\u95f4\u4e2d\u7814\u7a76\u8f83\u5c11\u3002\u4f20\u7edf\u7684\u7ea7\u8054\u7ed3\u6784\u4f7f\u7528\u591a\u4e2a\u72ec\u7acb\u7684\u5b50\u7f51\u7edc\u6765\u987a\u5e8f\u5730\u7ec6\u5316\u533a\u57df\u5efa\u8bae\u3002\u7136\u800c\uff0c\u8fd9\u79cd\u65b9\u6cd5\u5728\u6240\u6709\u9636\u6bb5\u6d4b\u91cf\u63d0\u6848\u8d28\u91cf\u7684\u80fd\u529b\u6709\u9650\uff0c\u5e76\u4e14\u5f88\u96be\u57283D\u7a7a\u95f4\u4e2d\u5b9e\u73b0\u671f\u671b\u7684\u6027\u80fd\u6539\u8fdb\u3002\u6211\u4eec\u4f7f\u7528\u4e86\u4e00\u79cd\u65b0\u7684\u7ea7\u8054\u6846\u67b6\uff0c\u79f0\u4e3a\u7ea7\u8054\u6ce8\u610f\uff08CasA\uff09\uff0c\u7528\u4e8e\u4ece\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u4e2d\u68c0\u6d4b\u4e09\u7ef4\u7269\u4f53\u3002CasA\u7531\u533a\u57df\u5efa\u8bae\u7f51\u7edc\uff08RPN\uff09\u548c\u7ea7\u8054\u7ec6\u5316\u7f51\u7edc\uff08CRN\uff09\u7ec4\u6210\u3002\u5728CRN\u4e2d\uff0c\u6211\u4eec\u8bbe\u8ba1\u4e86\u4e00\u79cd\u65b0\u7684\u7ea7\u8054\u6ce8\u610f\u529b\u6a21\u5757\uff08CAM\uff09\uff0c\u8be5\u6a21\u5757\u4f7f\u7528\u591a\u4e2a\u5b50\u7f51\u7edc\u548c\u6ce8\u610f\u529b\u6a21\u5757\u6765\u805a\u5408\u4e0d\u540c\u9636\u6bb5\u7684\u5bf9\u8c61\u7279\u5f81\uff0c\u5e76\u9010\u6b65\u7ec6\u5316\u533a\u57df\u5efa\u8bae\u3002CasA\u53ef\u4ee5\u96c6\u6210\u5230\u5404\u79cd\u4e24\u7ea7\u4e09\u7ef4\u63a2\u6d4b\u5668\u4e2d\uff0c\u5e76\u63d0\u9ad8\u5176\u6027\u80fd\u3002<\/p>\n

Q\uff1a\u53c2\u8d5b\u611f\u53d7\u662f\u4ec0\u4e48\uff1f<\/p>\n

A\uff1a\u53c2\u52a0\u7b97\u6cd5\u6311\u6218\u8d5b\u8ba9\u6211\u4eec\u83b7\u5f97\u4e86\u8bb8\u591a\u5b9d\u8d35\u7684\u611f\u53d7\u548c\u7ecf\u9a8c\u3002\u5728\u6311\u6218\u8d5b\u4e2d\uff0c\u6211\u4eec\u5b66\u4f1a\u4e86\u66f4\u597d\u5730\u601d\u8003\u95ee\u9898\u548c\u89e3\u51b3\u95ee\u9898\u7684\u80fd\u529b\u3002\u6bd4\u8d5b\u4e2d\u9047\u5230\u7684\u5404\u79cd\u95ee\u9898\uff0c\u4ece\u6570\u636e\u5904\u7406\u5230\u6a21\u578b\u9009\u62e9\uff0c\u90fd\u8ba9\u6211\u4eec\u6df1\u5165\u7406\u89e3\u4e86\u7b97\u6cd5\u548c\u6570\u636e\u79d1\u5b66\u7684\u5b9e\u9645\u5e94\u7528\u3002\u9996\u5148\uff0c\u6311\u6218\u8d5b\u8ba9\u6211\u4eec\u638c\u63e1\u4e86\u66f4\u591a\u7684\u7b97\u6cd5\u548c\u6570\u636e\u7ed3\u6784\u77e5\u8bc6\uff0c\u8fd9\u5bf9\u6211\u4eec\u4eca\u540e\u7684\u79d1\u7814\u548c\u5de5\u4f5c\u90fd\u662f\u5fc5\u8981\u7684\u57fa\u7840\u3002\u5176\u6b21\uff0c\u901a\u8fc7\u6bd4\u8d5b\u83b7\u5f97\u7684\u7ecf\u9a8c\u53ef\u4ee5\u5e2e\u52a9\u6211\u5e94\u5bf9\u5404\u79cd\u96be\u9898\u548c\u6311\u6218\uff0c\u63d0\u9ad8\u89e3\u51b3\u95ee\u9898\u7684\u80fd\u529b\u548c\u6548\u7387\u3002\u6700\u540e\uff0c\u53c2\u52a0\u7b97\u6cd5\u6311\u6218\u8d5b\u8fd8\u80fd\u81ea\u5df1\u63a5\u89e6\u5230\u6765\u81ea\u4e0d\u540c\u9886\u57df\u548c\u56fd\u5bb6\u7684\u4f18\u79c0\u9009\u624b\uff0c\u6269\u5c55\u81ea\u5df1\u7684\u4eba\u8109\u548c\u89c6\u91ce\u3002<\/p>\n

\u6211\u60f3\u8bf4<\/p>\n

\u201c\u901a\u8fc7\u8f66\u8def\u534f\u540c\u7b97\u6cd5\u6311\u6218\u8d5b\uff0c\u79ef\u7d2f\u4e86\u5bf9\u524d\u6cbf\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u7ecf\u9a8c\uff0c\u5c24\u5176\u662f\u5728\u591a\u6a21\u578b\u878d\u5408\u3001\u591a\u6a21\u6001\u611f\u77e5\u7b49\u65b9\u9762\uff0c\u611f\u8c22\u4e3b\u529e\u65b9\u5bf9\u6bd4\u8d5b\u7684\u7cbe\u5fc3\u8bbe\u8ba1\uff0c\u4e5f\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684baseline\u4ee3\u7801\uff0c\u6a21\u578b\u7b49\u53ef\u4f9b\u53c2\u8003\u3002\u201d<\/p>\n

—\u56e2\u961f\uff1aARM330\uff08\u4e09\u7b49\u5956\uff09<\/p>\n

\u201c\u53c2\u52a0\u7b97\u6cd5\u6311\u6218\u8d5b\u662f\u4e00\u4e2a\u5f88\u597d\u7684\u673a\u4f1a\u6765\u953b\u70bc\u81ea\u5df1\u7684\u7b97\u6cd5\u8bbe\u8ba1\u548c\u7f16\u7a0b\u80fd\u529b\uff0c\u5e76\u4e14\u80fd\u591f\u63a5\u89e6\u5230\u6700\u65b0\u7684\u6280\u672f\u548c\u7814\u7a76\u65b9\u5411\u3002\u5728\u6311\u6218\u8d5b\u4e2d\uff0c\u6211\u4eec\u5b66\u5230\u4e86\u5f88\u591a\u5173\u4e8e\u8f66\u8def\u534f\u540c\u611f\u77e5\u7b97\u6cd5\u7684\u77e5\u8bc6\u548c\u6280\u80fd\uff0c\u4f8b\u5982\u6570\u636e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u3001\u6a21\u578b\u8bbe\u8ba1\u548c\u4f18\u5316\u7b49\u7b49\u3002\u540c\u65f6\uff0c\u6211\u4eec\u4e5f\u8ba4\u8bc6\u4e86\u8bb8\u591a\u6765\u81ea\u4e0d\u540c\u80cc\u666f\u548c\u9886\u57df\u7684\u4eba\uff0c\u8fd9\u4e9b\u4eba\u90fd\u5bf9\u7b97\u6cd5\u548c\u4eba\u5de5\u667a\u80fd\u6709\u7740\u6d53\u539a\u7684\u5174\u8da3\u548c\u70ed\u60c5\u3002<\/p>\n

\u53c2\u52a0\u6311\u6218\u8d5b\u5bf9\u4e8e\u4eca\u540e\u7684\u79d1\u7814\u548c\u5de5\u4f5c\u4e5f\u6709\u5f88\u5927\u7684\u5e2e\u52a9\u3002\u9996\u5148\uff0c\u5b83\u4f7f\u6211\u4eec\u66f4\u52a0\u4e86\u89e3\u4e86\u4eba\u5de5\u667a\u80fd\u5728\u4ea4\u901a\u9886\u57df\u7684\u5e94\u7528\u548c\u524d\u6cbf\u7814\u7a76\uff0c\u4e3a\u6211\u4eec\u4eca\u540e\u5728\u76f8\u5173\u9886\u57df\u7684\u7814\u7a76\u548c\u5de5\u4f5c\u63d0\u4f9b\u4e86\u5f88\u597d\u7684\u57fa\u7840\u3002\u5176\u6b21\uff0c\u5b83\u953b\u70bc\u4e86\u6211\u4eec\u5728\u7b97\u6cd5\u8bbe\u8ba1\u548c\u7f16\u7a0b\u65b9\u9762\u7684\u80fd\u529b\uff0c\u4f7f\u6211\u4eec\u66f4\u52a0\u81ea\u4fe1\u548c\u719f\u7ec3\u5730\u5e94\u5bf9\u672a\u6765\u7684\u6311\u6218\u3002\u6700\u540e\uff0c\u53c2\u52a0\u6311\u6218\u8d5b\u8fd8\u4f7f\u6211\u4eec\u610f\u8bc6\u5230\u4e86\u56e2\u961f\u534f\u4f5c\u548c\u6c9f\u901a\u7684\u91cd\u8981\u6027\uff0c\u8fd9\u5bf9\u4e8e\u4eca\u540e\u7684\u5de5\u4f5c\u548c\u751f\u6d3b\u90fd\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002\u201d<\/p>\n

—\u56e2\u961f\uff1aZLQK\uff08\u4e09\u7b49\u5956\uff09<\/p>\n

\u901a\u8fc7\u8f66\u8def\u534f\u540c\u7b97\u6cd5\u6311\u6218\u8d5b\uff0c\u6211\u4eec\u66f4\u52a0\u4e86\u89e3\u4e86\u81ea\u5df1\u7684\u7814\u7a76\u9886\u57df\uff0c\u5bf9\u81ea\u52a8\u9a7e\u9a76\u524d\u6cbf\u7684\u4e09\u7ef4\u611f\u77e5\u7b97\u6cd5\u53c8\u6709\u4e86\u66f4\u6df1\u523b\u7684\u7406\u89e3\u3002\u8fd9\u6b21\u6bd4\u8d5b\u8ba9\u6211\u4eec\u5bf9\u4ece\u8c03\u7814\u524d\u4eba\u5de5\u4f5c\u3001\u6a21\u578b\u9009\u62e9\u3001\u4ee3\u7801\u5b9e\u73b0\u7b97\u6cd5\u548c\u8bad\u7ec3\u4e0e\u6d4b\u8bd5\u90fd\u6709\u4e86\u66f4\u4e30\u5bcc\u7684\u7ecf\u9a8c\uff0c\u6b64\u5916\u6211\u4eec\u4e5f\u9996\u6b21\u901a\u8fc7\u672c\u6b21\u6bd4\u8d5b\u8ba4\u8bc6\u5230\u8def\u7aef\u548c\u8f66\u7aef\u68c0\u6d4b\u65b9\u6cd5\u7684\u5f02\u540c\u3002<\/p>\n

—-\u56e2\u961f\uff1a\u5927\u6a58\u592a\u91cd\u4e86\u7684\u56e2\u961f\uff08\u4e09\u7b49\u5956\uff09<\/p>\n

\u611f\u8c22\u6240\u6709\u7684\u53c2\u8d5b\u56e2\u961f\uff0c\u5e76\u795d\u8d3a\u4e0a\u699c\u961f\u4f0d\uff01<\/p>\n

\u5927\u8d5b\u53c2\u4e0e\u65b9<\/p>\n

\u6e05\u534eAIR<\/p>\n

\u6e05\u534e\u5927\u5b66\u667a\u80fd\u4ea7\u4e1a\u7814\u7a76\u9662\uff08Institute for AI Industry Research, Tsinghua University\uff0c\u82f1\u6587\u7b80\u79f0 AIR\uff09\u662f\u9762\u5411\u7b2c\u56db\u6b21\u5de5\u4e1a\u9769\u547d\u7684\u56fd\u9645\u5316\u3001\u667a\u80fd\u5316\u3001\u4ea7\u4e1a\u5316\u7684\u7814\u7a76\u673a\u6784\u3002AIR \u7684\u4f7f\u547d\u662f\u5229\u7528\u4eba\u5de5\u667a\u80fd\u6280\u672f\u8d4b\u80fd\u4ea7\u4e1a\u5347\u7ea7\u3001\u63a8\u52a8\u793e\u4f1a\u8fdb\u6b65\u3002\u901a\u8fc7\u5927\u5b66\u4e0e\u4f01\u4e1a\u521b\u65b0\u53cc\u5f15\u64ce\uff0c\u7a81\u7834\u4eba\u5de5\u667a\u80fd\u6838\u5fc3\u6280\u672f\uff0c\u57f9\u517b\u667a\u80fd\u4ea7\u4e1a\u9886\u519b\u4eba\u624d\uff0c\u63a8\u52a8\u667a\u80fd\u4ea7\u4e1a\u8de8\u8d8a\u5f0f\u53d1\u5c55\u3002<\/p>\n

\u767e\u5ea6Apollo<\/p>\n

\u767e\u5ea62013\u5e74\u5f00\u59cb\u5e03\u5c40\u81ea\u52a8\u9a7e\u9a76\uff0c2017\u5e74\u63a8\u51fa\u5168\u7403\u9996\u4e2a\u81ea\u52a8\u9a7e\u9a76\u5f00\u653e\u5e73\u53f0Apollo\u3002\u76ee\u524d\u767e\u5ea6Apollo\u5df2\u7ecf\u5728\u81ea\u52a8\u9a7e\u9a76\u3001\u667a\u80fd\u6c7d\u8f66\u3001\u667a\u80fd\u4ea4\u901a\u4e09\u5927\u9886\u57df\u62e5\u6709\u4e1a\u5185\u9886\u5148\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u662f\u5168\u7403\u667a\u80fd\u9a7e\u9a76\u4ea7\u4e1a\u7684\u9886\u8dd1\u8005\u3002<\/p>\n

\u98de\u6868<\/p>\n

\u672c\u6b21\u6bd4\u8d5b\u5e73\u53f0\u4e3a\u767e\u5ea6\u98de\u6868AI Studio\u3002\u98de\u6868\uff08PaddlePaddle\uff09\u4ee5\u767e\u5ea6\u591a\u5e74\u7684\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u7814\u7a76\u548c\u4e1a\u52a1\u5e94\u7528\u4e3a\u57fa\u7840\uff0c\u96c6\u6df1\u5ea6\u5b66\u4e60\u6838\u5fc3\u8bad\u7ec3\u548c\u63a8\u7406\u6846\u67b6\u3001\u57fa\u7840\u6a21\u578b\u5e93\u3001\u7aef\u5230\u7aef\u5f00\u53d1\u5957\u4ef6\u3001\u4e30\u5bcc\u7684\u5de5\u5177\u7ec4\u4ef6\u4e8e\u4e00\u4f53\uff0c\u662f\u4e2d\u56fd\u9996\u4e2a\u81ea\u4e3b\u7814\u53d1\u3001\u529f\u80fd\u4e30\u5bcc\u3001\u5f00\u6e90\u5f00\u653e\u7684\u4ea7\u4e1a\u7ea7\u6df1\u5ea6\u5b66\u4e60\u5e73\u53f0\u3002\u622a\u81f32022\u5e745\u6708\uff0c\u98de\u6868\u5df2\u7d2f\u8ba1\u51dd\u805a477\u4e07\u5f00\u53d1\u8005\u3001\u670d\u52a118\u4e07\u4f01\u4e8b\u4e1a\u5355\u4f4d\u3001\u521b\u5efa56\u4e07 AI \u6a21\u578b\u30022022\u5e747\u6708\uff0c\u4e2d\u56fd\u4fe1\u901a\u9662\u6700\u65b0\u62a5\u544a\u663e\u793a\uff0c\u767e\u5ea6\u98de\u6868\u6df1\u5ea6\u5b66\u4e60\u5e73\u53f0\u5c45\u4e2d\u56fd\u5e02\u573a\u5e94\u7528\u89c4\u6a21\u7b2c\u4e00\u3002\u98de\u6868\u52a9\u529b\u5f00\u53d1\u8005\u5feb\u901f\u5b9e\u73b0 AI \u60f3\u6cd5\uff0c\u521b\u65b0 AI \u5e94\u7528\uff0c\u4f5c\u4e3a\u57fa\u7840\u5e73\u53f0\u652f\u6491\u8d8a\u6765\u8d8a\u591a\u884c\u4e1a\u5b9e\u73b0\u4ea7\u4e1a\u667a\u80fd\u5316\u5347\u7ea7\u3002<\/p>\n

\u5e73\u53f0\u53ca\u8bba\u6587<\/p>\n

MMDetection3D<\/p>\n

MMDetection 3D \u662f OpenMMLab \u4e0b\u4e00\u4ee3\u901a\u7528 3D \u611f\u77e5\uff08\u68c0\u6d4b \/ \u5206\u5272\uff09\u5e73\u53f0\u3002\u5f97\u76ca\u4e8e\u5404\u79cd\u4ee3\u7801\u5c42\u9762\u7684\u4f18\u5316\uff0cMMDetection3D \u62e5\u6709\u4e1a\u754c\u6700\u5feb\u7684\u8bad\u7ec3\u901f\u5ea6\uff0c\u8986\u76d6\u4e86\u5355\u6a21\u6001\uff08\u70b9\u4e91 \/ \u56fe\u7247\uff09\u548c\u591a\u6a21\u6001 3D \u68c0\u6d4b\u4ee5\u53ca\u70b9\u4e91\u5206\u5272\uff0c\u5ba4\u5185\u548c\u5ba4\u5916\u573a\u666fSOTA\uff0c\u540c\u65f6\u652f\u6301\u4e86\u5404\u79cd\u5ba4\u5185\u5ba4\u5916\u5305\u62ec SUN RGB-D, ScanNet, nuScenes, Lyft, KITTI \u548c Waymo \u5728\u5185\u7684\u4e3b\u6d41\u6570\u636e\u96c6\u3002\u57fa\u4e8e MMDetection\uff0cMMDetection3D \u80fd\u591f\u65e0\u7f1d\u4f7f\u7528 MMDetection \u6240\u6709\u68c0\u6d4b\u5206\u5272\u7b97\u6cd5\uff0c\u6781\u5927\u65b9\u4fbf\u4e86\u591a\u6a21\u6001\u7b97\u6cd5\u7684\u7814\u53d1\u3002\u9664\u6b64\u4ee5\u5916\uff0c\u6700\u65b0\u7248\u7684 MMDetection3D \u63d0\u4f9b\u4e86\u5f00\u653e\u7edf\u4e00\u7684\u5750\u6807\u7cfb\u63a5\u53e3\uff0c\u4ece\u6570\u636e\u96c6\u3001\u4efb\u52a1\u3001\u6a21\u6001\u4e09\u4e2a\u65b9\u9762\u8fdb\u884c\u4e86\u7edf\u4e00\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u591a\u6a21\u6001\u53ef\u89c6\u5316\u80fd\u529b\uff0c\u540c\u65f6\u589e\u52a0\u4e86\u5bf9\u7eaf\u89c6\u89c9 (BEV) 3D \u89c6\u89c9\u611f\u77e5\u6a21\u578b\u7684\u5b8c\u5584\u652f\u6301\u3002https:\/\/github.com\/open-mmlab\/mmdetection3d<\/p>\n

OpenDAIRV2X<\/p>\n

OpenDAIRV2X\u662f\u6e05\u534e\u5927\u5b66\u667a\u80fd\u4ea7\u4e1a\u7814\u7a76\u9662\u5927\u6570\u636e\u5b9e\u9a8c\u5ba4\uff08DAIR Lab\uff09\u63a8\u51fa\u7684\u9762\u5411\u8f66\u8def\u534f\u540c\u81ea\u52a8\u9a7e\u9a76\u7684\u5f00\u6e90\u5e73\u53f0\u3002\u8be5\u5e73\u53f0\u81f4\u529b\u4e8e\u6253\u9020\u901a\u7528\u534f\u540c\u81ea\u52a8\u9a7e\u9a76\uff0c\u5168\u94fe\u6761\u8986\u76d6\u534f\u540c\u68c0\u6d4b\u3001\u8ddf\u8e2a\u3001\u9884\u6d4b\uff0c\u8fdb\u4e00\u6b65\u63a8\u52a8\u534f\u540c\u7684\u7aef\u5230\u7aef\u81ea\u52a8\u9a7e\u9a76\u53d1\u5c55\u3002\u57fa\u4e8e\u9996\u4e2a\u771f\u5b9e\u8f66\u8def\u534f\u540c\u573a\u666f\u7684DAIR-V2X\u7cfb\u5217\u6570\u636e\u96c6\uff0cOpenDAIRV2X\u76ee\u524d\u5df2\u63d0\u4f9b\u534f\u540c3D\u68c0\u6d4b\u76f8\u5173\u6570\u636e\u96c6API\uff0c\u5e76\u652f\u6301\u591a\u79cd\u4e0d\u540c\u878d\u5408\u7684\u534f\u540c\u68c0\u6d4b\u7b97\u6cd5\uff0c\u8fd1\u671f\u8fd8\u5c06\u652f\u6301\u534f\u540c\u8ddf\u8e2a\u548c\u9884\u6d4b\u76f8\u5173\u6570\u636e\u96c6V2X-Seq\u53ca\u76f8\u5173\u7b97\u6cd5\u3002https:\/\/github.com\/AIR-THU\/<\/p>\n

DAIR-V2XDAIR-V2X\u6570\u636e\u96c6\u8bba\u6587<\/p>\n

DAIR-V2X: A Large-scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection. Haibao Yu, Yizhen Luo, Mao Shu, Yiyi Huo, Zebang Yang, Yifeng Shi, Zhenglong Guo, Hanyu Li, Xing Hu, Jirui Yuan, and Zaiqing Nie. CVPR2022<\/p>\n","protected":false},"excerpt":{"rendered":"

3\u670823\u65e5\uff0c\u7531\u6e05\u534e\u5927\u5b66\u667a\u80fd\u4ea7\u4e1a\u7814\u7a76\u9662\uff08AIR\uff09 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[28,1],"tags":[],"class_list":["post-5155","post","type-post","status-publish","format-standard","hentry","category-professional-information","category-home"],"views":11,"_links":{"self":[{"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/posts\/5155"}],"collection":[{"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/comments?post=5155"}],"version-history":[{"count":3,"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/posts\/5155\/revisions"}],"predecessor-version":[{"id":5178,"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/posts\/5155\/revisions\/5178"}],"wp:attachment":[{"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/media?parent=5155"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/categories?post=5155"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/222.128.65.89:18086\/index.php\/wp-json\/wp\/v2\/tags?post=5155"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}