Search Results for author: Yuqi Li

Found 7 papers, 0 papers with code

ISP-Agnostic Image Reconstruction for Under-Display Cameras

no code implementations2 Nov 2021 Miao Qi, Yuqi Li, Wolfgang Heidrich

To obtain large quantities of real under-display camera training data with sufficient contrast and scene diversity, we furthermore develop a data capture method utilizing an HDR monitor, as well as a data augmentation method to generate suitable HDR content.

Data Augmentation Image Reconstruction +1

Multispectral Illumination Estimation Using Deep Unrolling Network

no code implementations ICCV 2021 Yuqi Li, Qiang Fu, Wolfgang Heidrich

This paper examines the problem of illumination spectra estimation in multispectral images.

A Set-Theoretic Study of the Relationships of Image Models and Priors for Restoration Problems

no code implementations29 Mar 2020 Bihan Wen, Yanjun Li, Yuqi Li, Yoram Bresler

Furthermore, we relate the denoising performance improvement by combining multiple models, to the image model relationships.

Denoising Image Restoration

Short-Term Temporal Convolutional Networks for Dynamic Hand Gesture Recognition

no code implementations31 Dec 2019 Yi Zhang, Chong Wang, Ye Zheng, Jieyu Zhao, Yuqi Li, Xijiong Xie

Subsequently, in temporal analysis, we use TCNs to extract temporal features and employ improved Squeeze-and-Excitation Networks (SENets) to strengthen the representational power of temporal features from each TCNs' layers.

Hand Gesture Recognition Hand-Gesture Recognition

GAN-based Projector for Faster Recovery with Convergence Guarantees in Linear Inverse Problems

no code implementations ICCV 2019 Ankit Raj, Yuqi Li, Yoram Bresler

A Generative Adversarial Network (GAN) with generator $G$ trained to model the prior of images has been shown to perform better than sparsity-based regularizers in ill-posed inverse problems.


Temporal Bilinear Networks for Video Action Recognition

no code implementations25 Nov 2018 Yanghao Li, Sijie Song, Yuqi Li, Jiaying Liu

Temporal modeling in videos is a fundamental yet challenging problem in computer vision.

Action Recognition

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