Search Results for author: Hui-Po Wang

Found 8 papers, 5 papers with code

ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training

1 code implementation11 Oct 2021 Hui-Po Wang, Sebastian U. Stich, Yang He, Mario Fritz

Federated learning is a powerful distributed learning scheme that allows numerous edge devices to collaboratively train a model without sharing their data.

Federated Learning Image Segmentation +2

Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling

1 code implementation CVPR 2021 Yan-Cheng Huang, Yi-Hsin Chen, Cheng-You Lu, Hui-Po Wang, Wen-Hsiao Peng, Ching-Chun Huang

Our Long Short-Term Memory Video Rescaling Network (LSTM-VRN) leverages temporal information in the low-resolution video to form an explicit prediction of the missing high-frequency information for upscaling.

CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization

no code implementations15 Dec 2020 Yang He, Hui-Po Wang, Maximilian Zenk, Mario Fritz

Despite notable progress in gradient compression, the existing quantization methods require further improvement when low-bits compression is applied, especially the overall systems often degenerate a lot when quantization are applied in double directions to compress model weights and gradients.

Federated Learning Image Classification +2

Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs

1 code implementation CVPR 2021 Hui-Po Wang, Ning Yu, Mario Fritz

While Generative Adversarial Networks (GANs) show increasing performance and the level of realism is becoming indistinguishable from natural images, this also comes with high demands on data and computation.

Image Generation Unconditional Image Generation

InfoScrub: Towards Attribute Privacy by Targeted Obfuscation

no code implementations20 May 2020 Hui-Po Wang, Tribhuvanesh Orekondy, Mario Fritz

Personal photos of individuals when shared online, apart from exhibiting a myriad of memorable details, also reveals a wide range of private information and potentially entails privacy risks (e. g., online harassment, tracking).

Attribute Translation

Learning Priors for Adversarial Autoencoders

no code implementations ICLR 2018 Hui-Po Wang, Wen-Hsiao Peng, Wei-Jan Ko

Most deep latent factor models choose simple priors for simplicity, tractability or not knowing what prior to use.

Image Generation Translation

All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation

1 code implementation CVPR 2019 Wei-Lun Chang, Hui-Po Wang, Wen-Hsiao Peng, Wei-Chen Chiu

In this paper we tackle the problem of unsupervised domain adaptation for the task of semantic segmentation, where we attempt to transfer the knowledge learned upon synthetic datasets with ground-truth labels to real-world images without any annotation.

Segmentation Semantic Segmentation +3

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