ACM #Multimedia 2021: Skeleton-Contrastive 3D Action Representation Learning w/ @fmthoker, @doughty_hazel: arxiv.org/abs/2108.03656 We learn invariances to multiple #skeleton representations and introduce various skeleton augmentations via noise contrastive estimation 1/n
Contribution I: leverage multiple input-representations of #3D-#skeleton sequences. Our inter-skeleton contrast learns from a pair of representations in a cross-contrastive fashion. Enriches the sparse input space and focuses on the high-level semantics of the skeleton data. 2/n
Feb 27, 2021 • 4 tweets • 5 min read
#ICLR2021 cam-ready II: "LiftPool: Bidirectional ConvNet Pooling" w/ Jiaojiao Zhao is now available: isis-data.science.uva.nl/cgmsnoek/pub/z… No more lossy down- and upsampling when pooling! 1/n
LiftPool adopts the philosophy of the classical #Lifting#Scheme from #signal#processing. LiftDownPool decomposes a feature map into various downsized sub-bands, each of which contains information with different frequencies. Because of its invertible properties, ... 2/n