1 code implementation • 16 Oct 2024 • Cheng Yu, Haoyu Xie, Lei Shang, Yang Liu, Jun Dan, Liefeng Bo, Baigui Sun
As a result, FACT solely learns identity preservation from training data, thereby minimizing the impact on the original text-to-image capabilities of the base model.
1 code implementation • 28 May 2024 • Ziheng Qin, Zhaopan Xu, Yukun Zhou, Zangwei Zheng, Zebang Cheng, Hao Tang, Lei Shang, Baigui Sun, Xiaojiang Peng, Radu Timofte, Hongxun Yao, Kai Wang, Yang You
To tackle this challenge, we propose InfoGrowth, an efficient online algorithm for data cleaning and selection, resulting in a growing dataset that keeps up to date with awareness of cleanliness and diversity.
1 code implementation • CVPR 2024 • Pengchong Qiao, Lei Shang, Chang Liu, Baigui Sun, Xiangyang Ji, Jie Chen
In this paper, motivated by object-oriented programming, we model the subject as a derived class whose base class is its semantic category.
1 code implementation • 28 Aug 2023 • Yang Liu, Cheng Yu, Lei Shang, Yongyi He, Ziheng Wu, Xingjun Wang, Chao Xu, Haoyu Xie, Weida Wang, Yuze Zhao, Lin Zhu, Chen Cheng, Weitao Chen, Yuan YAO, Wenmeng Zhou, Jiaqi Xu, Qiang Wang, Yingda Chen, Xuansong Xie, Baigui Sun
In this paper, we present FaceChain, a personalized portrait generation framework that combines a series of customized image-generation model and a rich set of face-related perceptual understanding models (\eg, face detection, deep face embedding extraction, and facial attribute recognition), to tackle aforementioned challenges and to generate truthful personalized portraits, with only a handful of portrait images as input.
1 code implementation • 8 Mar 2023 • Ziheng Qin, Kai Wang, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Daquan Zhou, Lei Shang, Baigui Sun, Xuansong Xie, Yang You
To solve this problem, we propose \textbf{InfoBatch}, a novel framework aiming to achieve lossless training acceleration by unbiased dynamic data pruning.
1 code implementation • ICCV 2023 • Zelin Zang, Lei Shang, Senqiao Yang, Fei Wang, Baigui Sun, Xuansong Xie, Stan Z. Li
The SCL loss weakens the adverse effects of the data augmentation view-noise problem which is amplified in domain transfer tasks.
Ranked #3 on
Universal Domain Adaptation
on Office-31
no code implementations • 2 Dec 2022 • Lei Shang, Mouxiao Huang, Wu Shi, Yuchen Liu, Yang Liu, Fei Wang, Baigui Sun, Xuansong Xie, Yu Qiao
Intuitively, FR algorithms can benefit from both the estimation of uncertainty and the detection of out-of-distribution (OOD) samples.
no code implementations • 21 Nov 2022 • Zelin Zang, Lei Shang, Senqiao Yang, Fei Wang, Baigui Sun, Xuansong Xie, Stan Z. Li
The SCL loss weakens the adverse effects of the data augmentation view-noise problem which is amplified in domain transfer tasks.
1 code implementation • 21 Nov 2022 • Zelin Zang, Shenghui Cheng, Linyan Lu, Hanchen Xia, Liangyu Li, Yaoting Sun, Yongjie Xu, Lei Shang, Baigui Sun, Stan Z. Li
The proposed techniques are integrated with a visual interface to help the user to adjust EVNet to achieve better DR performance and explainability.
2 code implementations • 7 Jul 2022 • Zelin Zang, Siyuan Li, Di wu, Ge Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li
To overcome the underconstrained embedding problem, we design a loss and theoretically demonstrate that it leads to a more suitable embedding based on the local flatness.
Ranked #2 on
Image Classification
on ImageNet-100
no code implementations • 29 Sep 2021 • Yang Liu, Zhipeng Zhou, Lei Shang, Baigui Sun, Hao Li, Rong Jin
Unsupervised domain adaptation (UDA) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain.
no code implementations • 1 Sep 2021 • Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin
In this work we develop a simple yet powerful framework, whose key idea is to select a subset of training examples from the unlabeled data when performing existing SSL methods so that only the unlabeled examples with pseudo labels related to the labeled data will be used to train models.
5 code implementations • ICCV 2019 • Qi Qian, Lei Shang, Baigui Sun, Juhua Hu, Hao Li, Rong Jin
The set of triplet constraints has to be sampled within the mini-batch.
Ranked #21 on
Metric Learning
on CUB-200-2011
(using extra training data)