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Min Jin Chong

7 accepted papers

2021

Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval

ICCV 2021poster

We present Retrieve in Style (RIS), an unsupervised framework for facial feature transfer and retrieval on real images. Recent work shows capabilities of transferring local facial features by capitalizing on the disentanglement property of the StyleGAN latent space. RIS improves existing art on the…

Cited by 31PDFcodeScholar
2021

Toward Accurate and Realistic Outfits Visualization With Attention to Details

CVPR 2021poster

Virtual try-on methods aim to generate images of fashion models wearing arbitrary combinations of garments. This is a challenging task because the generated image must appear realistic and accurately display the interaction between garments. Prior works produce images that are filled with artifacts…

Cited by 53PDFScholar
2020

Unrestricted Adversarial Examples via Semantic Manipulation

ICLR 2020poster

Machine learning models, especially deep neural networks (DNNs), have been shown to be vulnerable against adversarial examples which are carefully crafted samples with a small magnitude of the perturbation. Such adversarial perturbations are usually restricted by bounding their $\mathcal{L}_p$ norm…

Cited by 178SourceScholar
2017

EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms

NeurIPS 2017poster

This paper presents a probabilistic-graphical model that can be used to infer characteristics of instantaneous brain activity by jointly analyzing spatial and temporal dependencies observed in electroencephalograms (EEG). Specifically, we describe a factor-graph-based model with customized factor-fu…

Cited by 29SourcePDFScholar