Search Results for author: Kekai Sheng

Found 15 papers, 8 papers with code

Generative Domain Adaptation for Face Anti-Spoofing

no code implementations20 Jul 2022 Qianyu Zhou, Ke-Yue Zhang, Taiping Yao, Ran Yi, Kekai Sheng, Shouhong Ding, Lizhuang Ma

Most existing UDA FAS methods typically fit the trained models to the target domain via aligning the distribution of semantic high-level features.

Domain Adaptation Face Anti-Spoofing

Efficient Decoder-free Object Detection with Transformers

2 code implementations14 Jun 2022 Peixian Chen, Mengdan Zhang, Yunhang Shen, Kekai Sheng, Yuting Gao, Xing Sun, Ke Li, Chunhua Shen

A natural usage of ViTs in detection is to replace the CNN-based backbone with a transformer-based backbone, which is straightforward and effective, with the price of bringing considerable computation burden for inference.

Object Object Detection

Training-free Transformer Architecture Search

1 code implementation CVPR 2022 Qinqin Zhou, Kekai Sheng, Xiawu Zheng, Ke Li, Xing Sun, Yonghong Tian, Jie Chen, Rongrong Ji

Recently, Vision Transformer (ViT) has achieved remarkable success in several computer vision tasks.

ARM: Any-Time Super-Resolution Method

1 code implementation21 Mar 2022 Bohong Chen, Mingbao Lin, Kekai Sheng, Mengdan Zhang, Peixian Chen, Ke Li, Liujuan Cao, Rongrong Ji

To that effect, we construct an Edge-to-PSNR lookup table that maps the edge score of an image patch to the PSNR performance for each subnet, together with a set of computation costs for the subnets.

Image Super-Resolution

Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer

1 code implementation3 Aug 2021 Yifan Xu, Zhijie Zhang, Mengdan Zhang, Kekai Sheng, Ke Li, WeiMing Dong, Liqing Zhang, Changsheng Xu, Xing Sun

Vision transformers (ViTs) have recently received explosive popularity, but the huge computational cost is still a severe issue.

Image Classification

Dual Reweighting Domain Generalization for Face Presentation Attack Detection

no code implementations30 Jun 2021 Shubao Liu, Ke-Yue Zhang, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Yuan Xie, Lizhuang Ma

Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios.

Domain Generalization Face Anti-Spoofing +1

Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing

no code implementations6 May 2021 Zhihong Chen, Taiping Yao, Kekai Sheng, Shouhong Ding, Ying Tai, Jilin Li, Feiyue Huang, Xinyu Jin

Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios.

Domain Generalization Face Anti-Spoofing +2

Towards Corruption-Agnostic Robust Domain Adaptation

no code implementations21 Apr 2021 Yifan Xu, Kekai Sheng, WeiMing Dong, Baoyuan Wu, Changsheng Xu, Bao-Gang Hu

However, due to unpredictable corruptions (e. g., noise and blur) in real data like web images, domain adaptation methods are increasingly required to be corruption robust on target domains.

Domain Adaptation

On Evolving Attention Towards Domain Adaptation

no code implementations25 Mar 2021 Kekai Sheng, Ke Li, Xiawu Zheng, Jian Liang, WeiMing Dong, Feiyue Huang, Rongrong Ji, Xing Sun

However, considering that the configuration of attention, i. e., the type and the position of attention module, affects the performance significantly, it is more generalized to optimize the attention configuration automatically to be specialized for arbitrary UDA scenario.

Partial Domain Adaptation Unsupervised Domain Adaptation

Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation

no code implementations4 Dec 2020 Zhiyong Huang, Kekai Sheng, WeiMing Dong, Xing Mei, Chongyang Ma, Feiyue Huang, Dengwen Zhou, Changsheng Xu

For intra-domain propagation, we propose an effective self-training strategy to mitigate the noises in pseudo-labeled target domain data and improve the feature discriminability in the target domain.

Domain Adaptation Image Classification +1

Dynamic Refinement Network for Oriented and Densely Packed Object Detection

1 code implementation CVPR 2020 Xingjia Pan, Yuqiang Ren, Kekai Sheng, Wei-Ming Dong, Haolei Yuan, Xiaowei Guo, Chongyang Ma, Changsheng Xu

However, the detection of oriented and densely packed objects remains challenging because of following inherent reasons: (1) receptive fields of neurons are all axis-aligned and of the same shape, whereas objects are usually of diverse shapes and align along various directions; (2) detection models are typically trained with generic knowledge and may not generalize well to handle specific objects at test time; (3) the limited dataset hinders the development on this task.

feature selection object-detection +2

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

no code implementations26 Nov 2019 Kekai Sheng, Wei-Ming Dong, Menglei Chai, Guohui Wang, Peng Zhou, Feiyue Huang, Bao-Gang Hu, Rongrong Ji, Chongyang Ma

In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective.

Gourmet Photography Dataset for Aesthetic Assessment of Food Images

1 code implementation SIGGRAPH Asia 2018 2018 Kekai Sheng, Wei-Ming Dong, Haibin Huang, Chongyang Ma, Bao-Gang Hu

In this study, we present the Gourmet Photography Dataset (GPD), which is the first large-scale dataset for aesthetic assessment of food photographs.

Attention-based Multi-Patch Aggregation for Image Aesthetic Assessment

1 code implementation ACM Multimedia Conference 2018 Kekai Sheng, Wei-Ming Dong, Chongyang Ma, Xing Mei, Feiyue Huang, Bao-Gang Hu

Aggregation structures with explicit information, such as image attributes and scene semantics, are effective and popular for intelligent systems for assessing aesthetics of visual data.

Aesthetics Quality Assessment

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