Search Results for author: Yukai Shi

Found 14 papers, 3 papers with code

Heterogeneous Semantic Transfer for Multi-label Recognition with Partial Labels

1 code implementation23 May 2022 Tianshui Chen, Tao Pu, Lingbo Liu, Yukai Shi, Zhijing Yang, Liang Lin

Multi-label image recognition with partial labels (MLR-PL), in which some labels are known while others are unknown for each image, may greatly reduce the cost of annotation and thus facilitate large-scale MLR.

Exploring Negatives in Contrastive Learning for Unpaired Image-to-Image Translation

no code implementations23 Apr 2022 Yupei Lin, Sen Zhang, Tianshui Chen, Yongyi Lu, Guangping Li, Yukai Shi

Recently, contrastive learning (CL) has been used to further investigate the image correspondence in unpaired image translation by using patch-based positive/negative learning.

Contrastive Learning Image-to-Image Translation +1

Content-adaptive Representation Learning for Fast Image Super-resolution

no code implementations20 May 2021 Yukai Shi, Jinghui Qin

In contrast to existing studies that ignore difficulty diversity, we adopt different stage of a neural network to perform image restoration.

Image Restoration Image Super-Resolution +1

Unsupervised Multi-view Clustering by Squeezing Hybrid Knowledge from Cross View and Each View

no code implementations23 Aug 2020 Junpeng Tan, Yukai Shi, Zhijing Yang, Caizhen Wen, Liang Lin

To ensure that we achieve effective sparse representation and clustering performance on the original data matrix, adaptive graph regularization and unsupervised clustering constraints are also incorporated in the proposed model to preserve the internal structural features of the data.

DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-Resolution

1 code implementation25 Feb 2020 Yukai Shi, Haoyu Zhong, Zhijing Yang, Xiaojun Yang, Liang Lin

Previous image SR methods fail to exhibit similar performance on Real-SR as the image data is not aligned inherently.

Image Super-Resolution

Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning

no code implementations4 May 2019 Yukai Shi, Guanbin Li, Qingxing Cao, Keze Wang, Liang Lin

Face hallucination is a domain-specific super-resolution problem that aims to generate a high-resolution (HR) face image from a low-resolution~(LR) input.

Face Hallucination reinforcement-learning +1

Difficulty-aware Image Super Resolution via Deep Adaptive Dual-Network

1 code implementation11 Apr 2019 Jinghui Qin, Ziwei Xie, Yukai Shi, Wushao Wen

To identify whether a region is easy or hard, we propose a novel image difficulty recognition network based on PSNR prior.

Image Super-Resolution

Attention-Aware Face Hallucination via Deep Reinforcement Learning

no code implementations CVPR 2017 Qingxing Cao, Liang Lin, Yukai Shi, Xiaodan Liang, Guanbin Li

Face hallucination is a domain-specific super-resolution problem with the goal to generate high-resolution (HR) faces from low-resolution (LR) input images.

Face Hallucination reinforcement-learning +1

Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning

no code implementations26 Jul 2017 Yukai Shi, Keze Wang, Chongyu Chen, Li Xu, Liang Lin

Single image super resolution (SR), which refers to reconstruct a higher-resolution (HR) image from the observed low-resolution (LR) image, has received substantial attention due to its tremendous application potentials.

Image Restoration Image Super-Resolution +1

Local- and Holistic- Structure Preserving Image Super Resolution via Deep Joint Component Learning

no code implementations25 Jul 2016 Yukai Shi, Keze Wang, Li Xu, Liang Lin

Recently, machine learning based single image super resolution (SR) approaches focus on jointly learning representations for high-resolution (HR) and low-resolution (LR) image patch pairs to improve the quality of the super-resolved images.

Image Super-Resolution Representation Learning

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