{"id":6083,"date":"2023-06-12T15:30:31","date_gmt":"2023-06-12T07:30:31","guid":{"rendered":"https:\/\/www.neuvition.cn\/?p=6083"},"modified":"2023-06-21T09:43:41","modified_gmt":"2023-06-21T01:43:41","slug":"%e7%9b%ae%e6%a0%87%e6%a3%80%e6%b5%8b%e7%ae%97%e6%b3%95","status":"publish","type":"post","link":"https:\/\/www.neuvition.cn\/technology-blog\/%e7%9b%ae%e6%a0%87%e6%a3%80%e6%b5%8b%e7%ae%97%e6%b3%95.html","title":{"rendered":"\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5"},"content":{"rendered":"\n
\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff1a\u8fd9\u4e9b\u7b97\u6cd5\u8bc6\u522b\u70b9\u4e91\u6570\u636e\u4e2d\u611f\u5174\u8da3\u7684\u76ee\u6807\u5bf9\u8c61\uff0c\u4f8b\u5982\u6c7d\u8f66\u3001\u884c\u4eba\u6216\u4ea4\u901a\u6807\u5fd7\u3002<\/p>\n\n\n\n
\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\u7684\u5e94\u7528
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\u4ee5\u4e0b\u662f\u5341\u4e2a\u6d41\u884c\u7684\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\u5e93\uff0c\u4ee5\u53ca\u5b83\u4eec\u7684\u4e0b\u8f7d URL \u548c\u7b80\u8981\u8bf4\u660e\uff1a<\/p>\n\n\n\n
1. Open3D-ML (https:\/\/github.com\/isl-org\/Open3D-ML)\uff1aOpen3D-ML \u662f\u7528\u4e8e\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b493D\u673a\u5668\u5b66\u4e60\u4efb\u52a1\u7684\u5f00\u6e90\u5e93\u3002\u5b83\u5efa\u7acb\u5728 Open3D\u548c PyTorch \u4e4b\u4e0a\uff0c\u5305\u62ec\u6570\u636e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u548c\u6a21\u578b\u8bad\u7ec3\u7b49\u591a\u4e2a\u6a21\u5757\u3002<\/p>\n\n\n\n
2. PyTorch3D (https:\/\/github.com\/facebookresearch\/pytorch3d)\uff1aPyTorch3D \u662f\u4e00\u4e2a\u6d41\u884c\u7684\u5f00\u6e90\u5e93\uff0c\u7528\u4e8e3D\u6df1\u5ea6\u5b66\u4e60\u4efb\u52a1\uff0c\u5305\u62ec\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u3002\u5b83\u5305\u62ec\u5404\u79cd\u7528\u4e8e\u521b\u5efa3D\u6a21\u578b\u3001\u6e32\u67d3\u548c\u6267\u884c\u51e0\u4f55\u64cd\u4f5c\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
3. PointPillars (https:\/\/github.com\/nutonomy\/second.pytorch)\uff1aPointPillars \u662f\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u5b83\u4f7f\u7528\u70b9\u4e91\u7684\u7a00\u758f\u4f53\u7d20\u5316\u8868\u793a\u3002 \u8be5\u7b97\u6cd5\u5728 KITTI \u57fa\u51c6\u6570\u636e\u96c6\u4e0a\u53d6\u5f97\u4e86\u6700\u5148\u8fdb\u7684\u6027\u80fd\u3002<\/p>\n\n\n\n
4. SECOND (https:\/\/github.com\/nutonomy\/second.pytorch)\uff1aSECOND \u662f\u53e6\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u5b83\u4f7f\u7528\u4e0e PointPillars \u7c7b\u4f3c\u7684\u4f53\u7d20\u5316\u6280\u672f\u3002\u5b83\u5305\u62ec\u591a\u79cd\u9884\u5904\u7406\u548c\u540e\u5904\u7406\u5de5\u5177\uff0c\u5e76\u4e14\u4e5f\u5728 KITTI \u6570\u636e\u96c6\u4e0a\u53d6\u5f97\u4e86\u6700\u5148\u8fdb\u7684\u6027\u80fd\u3002<\/p>\n\n\n\n
5. PointNet (https:\/\/github.com\/charlesq34\/pointnet)\uff1aPointNet \u662f\u4e00\u79cd\u6d41\u884c\u7684\u6df1\u5ea6\u5b66\u4e60\u67b6\u6784\uff0c\u7528\u4e8e\u5904\u7406\u70b9\u4e91\u6570\u636e\uff0c\u5305\u62ec\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u3002\u5b83\u5305\u62ec\u7528\u4e8e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u548c\u5206\u7c7b\u4efb\u52a1\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
6. VoxelNet (https:\/\/github.com\/qianguih\/voxelnet)\uff1aVoxelNet\u662f\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u5b83\u4f7f\u7528\u4f53\u7d20\u5316\u548c3D\u5377\u79ef\u6765\u5904\u7406\u70b9\u4e91\u6570\u636e\u3002\u5b83\u5305\u62ec\u7528\u4e8e\u6570\u636e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u548c\u6a21\u578b\u8bad\u7ec3\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
7. LaserNet (https:\/\/github.com\/zccyman\/LaserNet)\uff1aLaserNet \u662f\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u5b83\u4f7f\u7528\u65f6\u7a7a\u7279\u5f81\u63d0\u53d6\u5668\u548c\u533a\u57df\u5efa\u8bae\u7f51\u7edc\u6765\u8bc6\u522b\u70b9\u4e91\u6570\u636e\u4e2d\u7684\u76ee\u6807\u3002\u5b83\u5305\u62ec\u7528\u4e8e\u6570\u636e\u9884\u5904\u7406\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
8. PIXOR (https:\/\/github.com\/philipptrenz\/PIXOR)\uff1aPIXOR \u662f\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u5b83\u4f7f\u7528\u70b9\u4e91\u7684\u9e1f\u77b0\u56fe\u8868\u793a\u3002\u5b83\u5305\u62ec\u7528\u4e8e\u6570\u636e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u548c\u6a21\u578b\u8bad\u7ec3\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
9. PV-RCNN (https:\/\/github.com\/open-mmlab\/OpenPCDet)\uff1aPV-RCNN \u662f\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u5b83\u4f7f\u7528\u4e24\u9636\u6bb5\u67b6\u6784\uff0c\u5305\u62ec\u7531\u9010\u70b9\u7279\u5f81\u7f16\u7801\u9636\u6bb5\u548c\u533a\u57df\u63d0\u6848\u9636\u6bb5\u3002 \u5b83\u5305\u62ec\u7528\u4e8e\u6570\u636e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u548c\u6a21\u578b\u8bad\u7ec3\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
10. SalsaNet (https:\/\/github.com\/ethz-asl\/salsanet)\uff1aSalsaNet\u662f\u4e00\u79cd\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u7b97\u6cd5\uff0c\u4f7f\u7528\u7a00\u758f3D\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u70b9\u4e91\u6570\u636e\u3002 \u5b83\u5305\u62ec\u7528\u4e8e\u6570\u636e\u9884\u5904\u7406\u3001\u7279\u5f81\u63d0\u53d6\u548c\u6a21\u578b\u8bad\u7ec3\u7684\u5de5\u5177\u3002<\/p>\n\n\n\n
\u8bf7\u6ce8\u610f\uff0c\u5176\u4e2d\u4e00\u4e9b\u5e93\u662f\u7814\u7a76\u539f\u578b\uff0c\u53ef\u80fd\u4e0d\u50cf\u5176\u4ed6\u5e93\u90a3\u6837\u6709\u636e\u53ef\u67e5\u6216\u7528\u6237\u53cb\u597d\u3002 \u6b64\u5916\uff0c\u53ef\u80fd\u8fd8\u6709\u5176\u4ed6\u5e93\u672a\u5305\u542b\u5728\u6b64\u5217\u8868\u4e2d\uff0c\u4f46\u8fd9\u4e9b\u5e93\u4e5f\u5f88\u6d41\u884c\u5e76\u4e14\u5bf9\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u76ee\u6807\u68c0\u6d4b\u5f88\u6709\u7528\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
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