?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Mass+Displacement+Networks&rft.creator=Neverova%2C+N&rft.creator=Kokkinos%2C+I&rft.description=Despite+the+large+improvements+in+performance+attained+by+deep+learning+in+computer%0D%0Avision%2C+one+can+often+further+improve+results+with+some+additional+post-processing%0D%0Athat+exploits+the+geometric+nature+of+the+underlying+task.+This+commonly+involves+displacing%0D%0Athe+posterior+distribution+of+a+CNN+in+a+way+that+makes+it+more+appropriate+for%0D%0Athe+task+at+hand%2C+e.g.+better+aligned+with+local+image+features%2C+or+more+compact.+In+this%0D%0Awork+we+integrate+this+geometric+post-processing+within+a+deep+architecture%2C+introducing%0D%0Aa+differentiable+and+probabilistically+sound+counterpart+to+the+common+geometric+voting%0D%0Atechnique+used+for+evidence+accumulation+in+vision.+We+refer+to+the+resulting+neural+models%0D%0Aas+Mass+Displacement+Networks+(MDNs)%2C+and+apply+them+to+human+pose+estimation%0D%0Ain+two+distinct+setups%3A+(a)+landmark+localization%2C+where+we+collapse+a+distribution+to+a%0D%0Apoint%2C+allowing+for+precise+localization+of+body+keypoints+and+(b)+communication+across%0D%0Abody+parts%2C+where+we+transfer+evidence+from+one+part+to+the+other%2C+allowing+for+a+globally%0D%0Aconsistent+pose+estimate.+We+evaluate+on+large-scale+pose+estimation+benchmarks%2C+such%0D%0Aas+MPII+Human+Pose+and+COCO+datasets%2C+and+report+systematic+improvements.&rft.publisher=BMVA+Press&rft.contributor=Shao%2C+L&rft.contributor=Shum%2C+HPH&rft.contributor=Hospedales%2C+T&rft.date=2018-09&rft.type=Proceedings+paper&rft.language=eng&rft.source=+++++In%3A+Shao%2C+L+and+Shum%2C+HPH+and+Hospedales%2C+T%2C+(eds.)+29th+British+Machine+Vision+Conference+(BMVC)+2018.++++BMVA+Press+(2018)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10060971%2F1%2F0060.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10060971%2F&rft.rights=open