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A Unified Framework for Compressive Video Recovery from Coded Exposure Techniques
PrasanShedligeri, AnupamaS, KaushikMitra....
Published date-11/11/2020
Several coded exposure techniques have been proposed for acquiring high frame rate videos at low bandwidth. Most recently, a Coded-2-Bucket camera has been proposed that can acquire two compressed measurements …
Continuous Perception for Classifying Shapes and Weights of Garmentsfor Robotic Vision Applications
LiDuan, GerardoAragon-Camarasa....
Published date-11/11/2020
We present an approach to continuous perception for robotic laundry tasks. Our assumption is that the visual prediction of a garment's shapes and weights is possible via a neural network …
EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels
RagavSachdeva, FilipeR.Cordeiro, VasileiosBelagiannis....
Published date-11/11/2020
The efficacy of deep learning depends on large-scale data sets that have been carefully curated with reliable data acquisition and annotation processes. However, acquiring such large-scale data sets with precise …
End-to-End Chinese Landscape Painting Creation Using Generative Adversarial Networks
AliceXue....
Published date-11/11/2020
ChineseLandscapePaintingGeneration
Current GAN-based art generation methods produce unoriginal artwork due to their dependence on conditional input. Here, we propose Sketch-And-Paint GAN (SAPGAN), the first model which generates Chinese landscape paintings from …
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
ZhanqiuZhang, JianyuCai, JieWang....
Published date-11/11/2020
KnowledgeGraphCompletion, LinkPrediction
Tensor factorization based models have shown great power in knowledge graph completion (KGC). However, their performance usually suffers from the overfitting problem seriously. This motivates various regularizers---such as the squared …
Probability-Density-Based Deep Learning Paradigm for the Fuzzy Design of Functional Metastructures
Ying-TaoLuo, Peng-QiLi, Dong-TingLi....
Published date-11/11/2020
In quantum mechanics, a norm squared wave function can be interpreted as the probability density that describes the likelihood of a particle to be measured in a given position or …