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20192025
most citedRethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator

36 citations · 90 across the 21 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

cs.CV2021★ 1 cited

Anonymization for Skeleton Action Recognition

Saemi Moon, Myeonghyeon Kim, Zhenyue Qin +2

Skeleton-based action recognition attracts practitioners and researchers due to the lightweight, compact nature of datasets. Compared with RGB-video-based action recognition, skele…

cs.LG2021

Robust Deep Learning from Crowds with Belief Propagation

Hoyoung Kim, Seunghyuk Cho, Dongwoo Kim +1

Crowdsourcing systems enable us to collect large-scale dataset, but inherently suffer from noisy labels of low-paid workers. We address the inference and learning problems using su…

cs.CV2021★ 4 cited

Informative Class Activation Maps

Zhenyue Qin, Dongwoo Kim, Tom Gedeon

We study how to evaluate the quantitative information content of a region within an image for a particular label. To this end, we bridge class activation maps with information theo…

cs.LG2021

Neural Network Classifier as Mutual Information Evaluator

Zhenyue Qin, Dongwoo Kim, Tom Gedeon

Cross-entropy loss with softmax output is a standard choice to train neural network classifiers. We give a new view of neural network classifiers with softmax and cross-entropy as…

cs.LG2021★ 2 cited

Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions

Zhenyue Qin, Yiqun Zhang Saeed Anwar, Dongwoo Kim +3

Most existing graph neural networks (GNNs) learn node embeddings using the framework of message passing and aggregation. Such GNNs are incapable of learning relative positions betw…

cs.CV2021★ 6 cited

Fusing Higher-order Features in Graph Neural Networks for Skeleton-based Action Recognition

Zhenyue Qin, Yang Liu, Pan Ji +5

Skeleton sequences are lightweight and compact, and thus are ideal candidates for action recognition on edge devices. Recent skeleton-based action recognition methods extract featu…

eess.IV2021★ 11 cited

Invertible Denoising Network: A Light Solution for Real Noise Removal

Yang Liu, Zhenyue Qin, Saeed Anwar +4

Invertible networks have various benefits for image denoising since they are lightweight, information-lossless, and memory-saving during back-propagation. However, applying inverti…

cs.RO2021★ 1 cited

Roughly Collected Dataset for Contact Force Sensing Catheter

Seunghyuk Cho, Minsoo Koo, Dongwoo Kim +4

With rise of interventional cardiology, Catheter Ablation Therapy (CAT) has established itself as a first-line solution to treat cardiac arrhythmia. Although CAT is a promising tec…