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Juyong Kim

3 accepted papers

2024

WHAM: Reconstructing World-grounded Humans with Accurate 3D Motion

CVPR 2024poster

The estimation of 3D human motion from video has progressed rapidly but current methods still have several key limitations. First most methods estimate the human in camera coordinates. Second prior work on estimating humans in global coordinates often assumes a flat ground plane and produces foot sl…

Cited by 75SourcePDFScholar
2021

Improving Compositional Generalization in Classification Tasks via Structure Annotations

ACL 2021short

Compositional generalization is the ability to generalize systematically to a new data distribution by combining known components. Although humans seem to have a great ability to generalize compositionally, state-of-the-art neural models struggle to do so. In this work, we study compositional genera…

Cited by 17SourcePDFScholar
2017

SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization

ICML 2017poster

We propose a novel deep neural network that is both lightweight and effectively structured for model parallelization. Our network, which we name as SplitNet, automatically learns to split the network weights into either a set or a hierarchy of multiple groups that use disjoint sets of features, by l…

Cited by 101SourcePDFScholar