no code implementations • 6 Apr 2024 • Yinchi Zhou, Tianqi Chen, Jun Hou, Huidong Xie, Nicha C. Dvornek, S. Kevin Zhou, David L. Wilson, James S. Duncan, Chi Liu, Bo Zhou
To reduce the required number of iterations and ensure robust performance, our method first obtains a conditional GAN-generated prior image that will be used for the efficient reverse translation with a DM in the subsequent step.
no code implementations • 23 Mar 2024 • Mengqi Zhou, Jun Hou, Chuanchen Luo, Yuxi Wang, Zhaoxiang Zhang, Junran Peng
Due to its great application potential, large-scale scene generation has drawn extensive attention in academia and industry.
no code implementations • 11 Mar 2024 • Sikai Bai, Jie Zhang, Shuaicheng Li, Song Guo, Jingcai Guo, Jun Hou, Tao Han, Xiaocheng Lu
Federated learning (FL) has emerged as a powerful paradigm for learning from decentralized data, and federated domain generalization further considers the test dataset (target domain) is absent from the decentralized training data (source domains).
no code implementations • 25 Jan 2024 • Bo Zhou, Jun Hou, Tianqi Chen, Yinchi Zhou, Xiongchao Chen, Huidong Xie, Qiong Liu, Xueqi Guo, Yu-Jung Tsai, Vladimir Y. Panin, Takuya Toyonaga, James S. Duncan, Chi Liu
Low-dose PET offers a valuable means of minimizing radiation exposure in PET imaging.
no code implementations • 11 Jul 2023 • Sikai Bai, Shuaicheng Li, Weiming Zhuang, Jie Zhang, Song Guo, Kunlin Yang, Jun Hou, Shuai Zhang, Junyu Gao, Shuai Yi
Theoretically, we show the convergence guarantee of the dual regulators.
1 code implementation • 2 Apr 2023 • Bo Zhou, Huidong Xie, Qiong Liu, Xiongchao Chen, Xueqi Guo, Zhicheng Feng, Jun Hou, S. Kevin Zhou, Biao Li, Axel Rominger, Kuangyu Shi, James S. Duncan, Chi Liu
While previous federated learning (FL) algorithms enable multi-institution collaborative training without the need of aggregating local data, addressing the large domain shift in the application of multi-institutional low-count PET denoising remains a challenge and is still highly under-explored.
1 code implementation • Conference 2022 • Wei Lin, Kunlin Yang, Xinzhu Ma, Junyu Gao, Lingbo Liu, Shinan Liu, Jun Hou, Shuai Yi, Antoni B. Chan
Here we propose a scale-sensitive generalized loss to tackle this problem.
Ranked #8 on Object Counting on FSC147
no code implementations • 15 Aug 2022 • Xinzhu Ma, Yuan Meng, Yinmin Zhang, Lei Bai, Jun Hou, Shuai Yi, Wanli Ouyang
We hope this work can provide insights for the image-based 3D detection community under a semi-supervised setting.
1 code implementation • 5 Jul 2022 • Weichen Fan, Jinghuan Chen, Jiabin Ma, Jun Hou, Shuai Yi
We evaluate our model in several I2I translation benchmarks, and the results show that the proposed model has advantages over previous methods in both strongly constrained and normally constrained tasks.
Ranked #1 on Style Transfer on WikiArt
no code implementations • 21 Jun 2022 • Shuaicheng Li, Feng Zhang, Kunlin Yang, Lingbo Liu, Shinan Liu, Jun Hou, Shuai Yi
Our proposed method mainly leverages the intra-modality encoding and cross-modality co-occurrence encoding for fully representation modeling.
1 code implementation • 21 Jun 2022 • Shuaicheng Li, Feng Zhang, Rui-Wei Zhao, Rui Feng, Kunlin Yang, Lingbo Liu, Jun Hou
Based on PRSlot modules, we present a novel Pyramid Region-based Slot Attention Network termed PRSA-Net to learn a unified visual representation with rich temporal and semantic context for better proposal generation.
1 code implementation • 13 Jun 2022 • Zengyu Qiu, Xinzhu Ma, Kunlin Yang, Chunya Liu, Jun Hou, Shuai Yi, Wanli Ouyang
Besides, our DPK makes the performance of the student model positively correlated with that of the teacher model, which means that we can further boost the accuracy of students by applying larger teachers.
no code implementations • 2 May 2022 • Zijian Ying, Qianmu Li, Zhichao Lian, Jun Hou, Tong Lin, Tao Wang
To organize these excitations into final saliency maps, we introduce a double-chain backpropagation procedure.
no code implementations • 2 Dec 2021 • Kun Yan, Chenbin Zhang, Jun Hou, Ping Wang, Zied Bouraoui, Shoaib Jameel, Steven Schockaert
A key feature of the multi-label setting is that images often have multiple labels, which typically refer to different regions of the image.
1 code implementation • ICCV 2021 • Shuaicheng Li, Qianggang Cao, Lingbo Liu, Kunlin Yang, Shinan Liu, Jun Hou, Shuai Yi
It captures spatial-temporal contextual information jointly to augment the individual and group representations effectively with a clustered spatial-temporal transformer.
1 code implementation • 29 Jul 2021 • Yinmin Zhang, Xinzhu Ma, Shuai Yi, Jun Hou, Zhihui Wang, Wanli Ouyang, Dan Xu
In this paper, we propose to learn geometry-guided depth estimation with projective modeling to advance monocular 3D object detection.
Ranked #10 on Monocular 3D Object Detection on KITTI Cars Moderate
1 code implementation • 19 Jul 2021 • Haopeng Li, Lingbo Liu, Kunlin Yang, Shinan Liu, Junyu Gao, Bin Zhao, Rui Zhang, Jun Hou
Video crowd localization is a crucial yet challenging task, which aims to estimate exact locations of human heads in the given crowded videos.
no code implementations • 28 Oct 2020 • Junzhe Shi, Bin Xu, Xingyu Zhou, Jun Hou
The Gradient Boost Decision Tree model is selected due to its best accuracy and high stability.
no code implementations • 27 Oct 2020 • Bin Xu, Jun Hou, Junzhe Shi, Huayi Li, Dhruvang Rathod, Zhe Wang, Zoran Filipi
This study aims to reduce the learning iterations of Q-learning in HEV application and improve fuel consumption in initial learning phases utilizing warm start methods.
no code implementations • 11 Feb 2020 • Jun Hou, Tong Qin, Kailiang Wu, Dongbin Xiu
A novel correction algorithm is proposed for multi-class classification problems with corrupted training data.
no code implementations • 4 Feb 2020 • Wenyang Hu, Xiaocong Cai, Jun Hou, Shuai Yi, Zhiping Lin
Extensive experiments on standard benchmarks demonstrate that our end-to-end model achieves a new state-of-the-art for regular and irregular scene text recognition and needs 6 times shorter inference time than attentionbased methods.
1 code implementation • 22 Oct 2018 • Bo Zhou, Xunyu Lin, Brendan Eck, Jun Hou, David L. Wilson
Dual-energy (DE) chest radiographs provide greater diagnostic information than standard radiographs by separating the image into bone and soft tissue, revealing suspicious lesions which may otherwise be obstructed from view.