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Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View Consistency
FangZhao, ShengcaiLiao, KaihaoZhang....
Published date-12/01/2020
HumanParsing, SemanticParsing, TextureSynthesis
This paper proposes a human parsing based texture transfer model via cross-view consistency learning to generate the texture of 3D human body from a single image. We use the semantic …
Continual Learning of a Mixed Sequence of Similar and Dissimilar Tasks
ZixuanKe, BingLiu, XingchangHuang....
Published date-12/01/2020
ContinualLearning, TransferLearning
Existing research on continual learning of a sequence of tasks focused on dealing with catastrophic forgetting, where the tasks are assumed to be dissimilar and have little shared knowledge. Some …
Digraph Inception Convolutional Networks
ZekunTong, YuxuanLiang, ChangshengSun....
Published date-12/01/2020
Graph Convolutional Networks (GCNs) have shown promising results in modeling graph-structured data. However, they have difficulty with processing digraphs because of two reasons: 1) transforming directed to undirected graph to …
H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks
ThomasLimbacher, RobertLegenstein....
Published date-12/01/2020
QuestionAnswering
The ability to base current computations on memories from the past is critical for many cognitive tasks such as story understanding. Hebbian-type synaptic plasticity is believed to underlie the retention …
Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning
ShreyasFadnavis, JoshuaBatson, EleftheriosGaryfallidis....
Published date-12/01/2020
Denoising, Self-SupervisedLearning
Diffusion-weighted magnetic resonance imaging (DWI) is the only non-invasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain. Fluctuations from multiple sources create significant noise in …
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
MichaelDennis, NatashaJaques, EugeneVinitsky....
Published date-12/01/2020
TransferLearning
A wide range of reinforcement learning (RL) problems --- including robustness, transfer learning, unsupervised RL, and emergent complexity --- require specifying a distribution of tasks or environments in which a …