activity
20192021
most citedSHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

5 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20212 cited

Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes

Jian-Wei Zhang, Lei Lv, Yawei Luo +3

Few-shot segmentation~(FSS) performance has been extensively promoted by introducing episodic training and class-wise prototypes. However, the FSS problem remains challenging due t…

cs.LG20205 cited

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

Hao-Zhe Feng, Kezhi Kong, Minghao Chen +3

Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference r…

cs.LG2020

KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation

Hao-Zhe Feng, Zhaoyang You, Minghao Chen +5

Conventional unsupervised multi-source domain adaptation (UMDA) methods assume all source domains can be accessed directly. This neglects the privacy-preserving policy, that is, al…

cs.HC2020

GraphFederator: Federated Visual Analysis for Multi-party Graphs

Dongming Han, Wei Chen, Rusheng Pan +8

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs. Inspired by…

cs.LG20191 cited

An Interactive Insight Identification and Annotation Framework for Power Grid Pixel Maps using DenseU-Hierarchical VAE

Tianye Zhang, Haozhe Feng, Zexian Chen +4

Insights in power grid pixel maps (PGPMs) refer to important facility operating states and unexpected changes in the power grid. Identifying insights helps analysts understand the…