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20182021
most citedKnowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays

6 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation

Qiusheng Huang, Zhilin Zheng, Xueqi Hu +2

The image-to-image translation (I2IT) model takes a target label or a reference image as the input, and changes a source into the specified target domain. The two types of synthesi…

cs.CV20206 cited

Knowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays

Yirui Wang, Kang Zheng, Chi-Tung Chang +7

Exploiting available medical records to train high performance computer-aided diagnosis (CAD) models via the semi-supervised learning (SSL) setting is emerging to tackle the prohib…

cs.CV2020

Learning Posterior and Prior for Uncertainty Modeling in Person Re-Identification

Yan Zhang, Zhilin Zheng, Binyu He +1

Data uncertainty in practical person reID is ubiquitous, hence it requires not only learning the discriminative features, but also modeling the uncertainty based on the input. This…

cs.CV2019

Disentangling the Spatial Structure and Style in Conditional VAE

Ziye Zhang, Li Sun, Zhilin Zheng +1

This paper aims to disentangle the latent space in cVAE into the spatial structure and the style code, which are complementary to each other, with one of them being label rel…

cs.CV2018

Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions

Zhilin Zheng, Li Sun

VAE requires the standard Gaussian distribution as a prior in the latent space. Since all codes tend to follow the same prior, it often suffers the so-called "posterior collapse".…