[{"data":1,"prerenderedAt":55},["ShallowReactive",2],{"rendered-post-28e012f":3},{"abbrlink":4,"title":5,"date":6,"categories":7,"tags":9,"excerpt":11,"htmlChunkEnds":12,"toc":14,"htmlGzip":54},"28e012f","GroupFormer简要学习笔记","2022-08-31",[8],"懵逼的深度学习",[10],"群体行为识别","摘要 快速记录下 GroupFormer 网络的核心思想。",[13],2575,[15,19,22,25,28,31,35,39,42,45,48,51],{"id":16,"text":17,"html":17,"level":18},"post-heading-摘要","摘要",2,{"id":20,"text":21,"html":21,"level":18},"post-heading-主要结构","主要结构",{"id":23,"text":24,"html":24,"level":18},"post-heading-特征提取器","特征提取器",{"id":26,"text":27,"html":27,"level":18},"post-heading-群体表示生成器","群体表示生成器",{"id":29,"text":30,"html":30,"level":18},"post-heading-聚类时空transformer","聚类时空Transformer",{"id":32,"text":33,"html":33,"level":34},"post-heading-时空transformer","时空Transformer",3,{"id":36,"text":37,"html":37,"level":38},"post-heading-encoders","Encoders",4,{"id":40,"text":41,"html":41,"level":38},"post-heading-individual-decoders","Individual Decoders",{"id":43,"text":44,"html":44,"level":38},"post-heading-group-decoder","Group Decoder",{"id":46,"text":47,"html":47,"level":34},"post-heading-clustered-attention-mechanism","Clustered Attention Mechanism",{"id":49,"text":50,"html":50,"level":18},"post-heading-网络优化","网络优化",{"id":52,"text":53,"html":53,"level":18},"post-heading-总结","总结","H4sIAAAAAAAAA51YW3MaRxZ+z69geXIeVKqN87SrpSqxd12prc1WxX7b2gcijS3KEmgRSpXfwBoGEAPCuiBphC4oIMaSBTjIyjAD4seoT\u002FfwxF9IuntoGoRctXmSZqb7XL5z+c5hbvErX2jhb\u002F6VyGpsZlEJLoTCr2bwu333POEP8L9zs4tfBb6YWwlA77IfP3HrTejuIivrexaNrK38IxJdVqI+0n1HnBIxVHxqQW8dx4\u002Fweusu\u002FnZudoXdXQmuKNG\u002FDJ\u002FmIwuK9zBNP7Ic9zxBnG18rPoD8pOw5U\u002F\u002FeRl6tRZV\u002FvzfR1xOZCnwxdxSKIA3C7BZdGta\u002F+zd\u002FFJohRgqybThNuGWTVKxiaHOrcaikfCrwJPvv0eWA+1f5ma9N3+dm10KcTFkx0R2HlkXqLsNWzqUbHzQ4IIgfQS1LOhFSRa5raDutqdi5wSnC3Bg+h4xhHw\u002FKCtRZVUJx4KxUCTse6aElWgwFokOOvqzH559+bB6cGxslvHeDXlvQ7JFWs6goxNHo7olhbClc0PvuegmDPLR4QJeRIPh1Zc8Wo+ePH\u002Fx4r7iWQbitIhwzzm2cGD6AxMvRFz+GQorsdD8av9MdetXxFknhvr4Kc8O36PvHj\u002F90oe6JWTZ3wbnX\u002F8YCSsPZ8FUTP3ToRb68X4DWXFkXUDJxGYZjrPIuvLQFHGTJRhq\u002F0yFikoKGnFU5NwMOjo0tbGAD\u002FEdxl+D9KXb\u002FYBzZ8iy3Zrm1jKxyGsl7F2tryPng5swoJBGTpXbKOt82GU5XrFRvPwPBdJze\u002FHxlBq+L2Ta9ccMNWTZ3EB87cCG6TaYh3Hdrd+69TKt6smrj2gCwdkxdGxkayL9OFrCWbhN3MXfQn0d9CTOfkBWhUamfeOWdVqXnSI5TcCBOeikedDIe7u\u002Fdy3ew5aO927kN75BJ0NRZiHwkGV3RkdZjKjW9g10diFZRXYFNjPEUD0raz97svBRlT9w75C1gawsLqZQr4wTjbv4W1yKQyFPa27H9AzknskiOAj8AzFUHmLR+Ra\u002Fvh8aJUz7X3TVH\u002Fi799\u002Fc7OLXLBD9VIolqzYG1dD737Upyz8qC8LSkbMlz0BIa3ingayrQUdH3ZIbT0oi2YETG9l5KZI0EOOwM6+uzlH71Et7Ct0kNtDUPMCda7DP3ZrGijo2v8hf0Ci1b8DeGWEnueF1tkwclzJg1YQNQo9EHbB5jqw4qeU4GpMZAen3ZMfkb2HDxPEEsXvk+ozHxb3dhmSV4zTo6P244fZS5CIBKRs3Nql\u002FzEX8S0\u002F2hnrMHPXa3FEVWU1oeLplIyes6Sc+we1kGtP62c6hbuku\u002FhZZeWRtuL3m\u002FTPIykFBR+0sVFQaT5tm3oR8aGreRQl1Dq+E\u002FWezLxReCP0UWlgLLs0sKMNE\u002FE689D1VJnKSpxFt9Smp1uUSIE4HCmk3vu4evJPLcWpRTdzniOHTFKS08awUR+j\u002FrBFRPI6qyN5yy1URdlmJnDWNNrLz3JqRsbSW7wFPcyRlswGj5J5dclB9wflYJOr735oSfXM\u002FDvIVYqisKim64vpr5Q1s6T8Fl9aUu\u002FhbSRZs6a+VN3fxBPvm9g7dsj4fjayuzgRjMSVMJwSqLrfr5n+Vk5rXE9eLD69xsQmFvFyZohcIBAo6Pv2VGCq9ytDg8v4PNCaKHFn5sexjxnMipDo2G5TuSlnULeH9hlCDuj2yQyWPYyK+CyXCFQ5hLLSsCPyJegOF\u002FFS4qM29FDGzIkxCNO0uG++p5ydVnLnlUyGyrrB6Aslr9+bn32MHVk0CTbR8aGpu74C3Yc4gY\u002FnIQBqFnSNxnINCmtEFG0s4MQjeGRIDF0tquQmxeL\u002FBkxrZGu\u002FSEz1RcNwo5obqNq5QOwPJlpvYEWwk8\u002FFnm8ErOqAO+4A\u002FwOdVrwOIBjCkUW06Bw466bF7g04GH1V5p5Vdn+BKgceEPNQ+4T3hgW7AWwFvpZA\u002FGT8Fug3pS9E9J0TD5gXoSShcQsWAyjXHH7dMrG7ikg3pGzbpMZbM5PrnaT62Uia1cvzic2Xp5cw3w8wbQTtlAJtfWluNKVFlYZSpM8vK\u002FGIwHFpd9geeDD\u002F7hDjfv4afxWDmHnRp5rNsgKTp9o5xvipb\u002FOBs5q53oXLCeVbQuFgiUFfjUxkULpGtuXULKgaycuTQgmRr4jzDmrX+bo\u002FP1J7wZAu3TEi2+jt1yuAMbEkFpQ06Dw\u002FtprYy02HjEB\u002F2vPGZTbbyJ29yaGp49xpZF1Tj0R6pNVE7K87f93mE5\u002FOVYCwUXJp5oSyvRKLBJZ90bNDR2erj88ZS1rJoc+R5ysoY0nQT8KxgBUkcFbQkHWwdlXa\u002FITD4qMobNSRN+Bjnw\u002FM0MuqfFyGZhqZHnlwDsuwnyLrgDo1aXL1M6nssC7O8TZCPDhxnBUKDjjG+8XLrhh\u002FToXAsGuSF7ZMoJeMbdAzYvMAlWp1u6oLOGizXuQGgJYmhShSFMznUMSihMV5n3oj1lOEgq1SiD6jkt2mOMTWonaU30wVotCmOG6f4aJ2nx0jDZ\u002FZQVpGosw960R+Qn0YbYOkDLqb4uEIMlYab0tJlA9JNctmgOBbb0Nn0ejZbUvkEzY6yydmjssNrnK8iJ39\u002F5ZS3JTpy7zapCEa4dMpkIzefW\u002FlMTgGme47OyZBq8gSN0wNtnGcq\u002FpQdleCGiboluN2DtEZ1MCIfMZPjwEZ5NOuvd\u002FvxDM6+p8XK1x7tE86dQOUjpLp4t0kzVk9Bo8NBG\u002FKm8fBKiuMOcbb9Af539FtQyeRAy6uGNCPSeR0Xm9SBaQsH+zGH5nytiSxb+iGJgl9fdxM7UEh7zcvWJqY8ARXOm7h4JceCTuRXFagUhU1ub1\u002Fwl9c7pPZJOemPVj+t+9s9fHgN1a5of\u002FJvTbRv8iZItzMaLhqBXL1\u002FqLEdgKqjXN\u002Fu4dYhFVs\u002F7l\u002FolBH5KFo28T5lMQkeb8HMN92bJKVXW4NKDSoG3m2SwzpkcsRQn\u002F\u002F7xTe42Mat3WEH+g0\u002F5n\u002Fa5RMAAA==",1793389735039]