1 code implementation • 11 Jan 2024 • Chunlei Peng, Boyu Wang, Decheng Liu, Nannan Wang, Ruimin Hu, Xinbo Gao
To address this, we mask the clothing and color information in the personal attribute description extracted through an attribute detection model.
1 code implementation • 16 Dec 2023 • Decheng Liu, Xu Luo, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao
In this paper, we propose a novel Symmetrical Bidirectional Knowledge Alignment for zero-shot sketch-based image retrieval (SBKA).
2 code implementations • 7 Dec 2023 • Chunlei Peng, Huiqing Guo, Decheng Liu, Nannan Wang, Ruimin Hu, Xinbo Gao
Considering the complexity of the quality distribution of both real and fake faces, we propose a novel Deepfake detection framework named DeepFidelity to adaptively distinguish real and fake faces with varying image quality by mining the perceptual forgery fidelity of face images.
no code implementations • 5 Nov 2023 • Decheng Liu, Jiahao Yu, Ruimin Hu, Wenbin Feng
Based on the proposed identity model, we propose a trustworthy identity tracing framework (TITF) with multi-attribute synergistic identification to determine the identity of unknown objects, which can optimize the core identification set and provide an interpretable identity tracing process.
1 code implementation • NeurIPS 2023 • Ruiying Lu, Yujie Wu, Long Tian, Dongsheng Wang, Bo Chen, Xiyang Liu, Ruimin Hu
First, instead of learning the continuous representations, we preserve the typical normal patterns as discrete iconic prototypes, and confirm the importance of Vector Quantization in preventing the model from falling into the shortcut.
1 code implementation • 21 Jul 2023 • Decheng Liu, Tao Chen, Chunlei Peng, Nannan Wang, Ruimin Hu, Xinbo Gao
Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security.
no code implementations • 8 Dec 2022 • Jing Fang, Yinbo Yu, Zhongyuan Wang, Xin Ding, Ruimin Hu
Image super-resolution (SR) is a technique to recover lost high-frequency information in low-resolution (LR) images.
no code implementations • 1 Dec 2022 • Linbo Luo, Yuanjing Li, Haiyan Yin, Shangwei Xie, Ruimin Hu, Wentong Cai
In this paper, we present a systematic study to tackle the important problem of VAD for CABs with a novel crowd motion learning framework, multi-scale motion consistency network (MSMC-Net).
no code implementations • 31 Jul 2020 • Xin Xu, Shiqin Wang, Zheng Wang, Xiaolong Zhang, Ruimin Hu
Low light images captured in a non-uniform illumination environment usually are degraded with the scene depth and the corresponding environment lights.
no code implementations • 10 Apr 2020 • Xin Xu, Lei Liu, Weifeng Liu, Meng Wang, Ruimin Hu
To alleviate such a problem, we present an active hard sample mining framework via training an effective re-ID model with the least labeling efforts.
no code implementations • 31 Jan 2020 • Chuang Wang, Ruimin Hu, Min Hu, Jiang Liu, Ting Ren, Shan He, Ming Jiang, Jing Miao
And we validate our method on the Aff-Wild2 datasets released by the Challenge.
Facial Expression Recognition Facial Expression Recognition (FER)
1 code implementation • 12 May 2019 • Junjun Jiang, Yi Yu, Zheng Wang, Suhua Tang, Ruimin Hu, Jiayi Ma
In this paper, we present a simple but effective single image SR method based on ensemble learning, which can produce a better performance than that could be obtained from any of SR methods to be ensembled (or called component super-resolvers).
no code implementations • 19 Aug 2018 • Pan Xiao, Bo Du, Jia Wu, Lefei Zhang, Ruimin Hu, Xuelong. Li
Many classic methods solve the domain adaptation problem by establishing a common latent space, which may cause the loss of many important properties across both domains.
no code implementations • CVPR 2015 • Xiao-Yuan Jing, Xiaoke Zhu, Fei Wu, Xinge You, Qinglong Liu, Dong Yue, Ruimin Hu, Baowen Xu
In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD^2L) approach for SR person re-identification.