1 code implementation • 1 Apr 2024 • Jiazheng Xing, Chao Xu, Yijie Qian, Yang Liu, Guang Dai, Baigui Sun, Yong liu, Jingdong Wang
However, the clothing identity uncontrollability and training inefficiency of existing diffusion-based methods, which struggle to maintain the identity even with full parameter training, are significant limitations that hinder the widespread applications.
no code implementations • 28 Mar 2024 • Mingze Sun, Chao Xu, Xinyu Jiang, Yang Liu, Baigui Sun, Ruqi Huang
Furthermore, we introduce the HoCo holistic communication dataset, which is a valuable resource for future research.
no code implementations • 13 Mar 2024 • Hongbin Xu, Weitao Chen, Feng Xiao, Baigui Sun, Wenxiong Kang
In this paper, we introduce StyleDyRF, a method that represents the 4D feature space by deforming a canonical feature volume and learns a linear style transformation matrix on the feature volume in a data-driven fashion.
1 code implementation • 11 Mar 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.
no code implementations • 8 Mar 2024 • Xiang Huang, Zhi-Qi Cheng, Jun-Yan He, Chenyang Li, Wangmeng Xiang, Baigui Sun, Xiao Wu
The advancement of autonomous driving systems hinges on the ability to achieve low-latency and high-accuracy perception.
1 code implementation • 4 Mar 2024 • Chao Xu, Yang Liu, Jiazheng Xing, Weida Wang, Mingze Sun, Jun Dan, Tianxin Huang, Siyuan Li, Zhi-Qi Cheng, Ying Tai, Baigui Sun
In this paper, we abstract the process of people hearing speech, extracting meaningful cues, and creating various dynamically audio-consistent talking faces, termed Listening and Imagining, into the task of high-fidelity diverse talking faces generation from a single audio.
no code implementations • 28 Feb 2024 • Haoyu Xie, Changqi Wang, Jian Zhao, Yang Liu, Jun Dan, Chong Fu, Baigui Sun
To address this issue, we propose a robust contrastive-based S4 framework, termed the Probabilistic Representation Contrastive Learning (PRCL) framework to enhance the robustness of the unsupervised training process.
2 code implementations • 14 Feb 2024 • Siyuan Li, Zicheng Liu, Juanxi Tian, Ge Wang, Zedong Wang, Weiyang Jin, Di wu, Cheng Tan, Tao Lin, Yang Liu, Baigui Sun, Stan Z. Li
Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DNN) optimization.
1 code implementation • 31 Dec 2023 • Siyuan Li, Luyuan Zhang, Zedong Wang, Di wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li
As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and the low dependence on labeled data.
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 • ICCV 2023 • Jun Dan, Yang Liu, Haoyu Xie, Jiankang Deng, Haoran Xie, Xuansong Xie, Baigui Sun
We investigate the reasons for this phenomenon and discover that the existing data augmentation approach and hard sample mining strategy are incompatible with ViTs-based FR backbone due to the lack of tailored consideration on preserving face structural information and leveraging each local token information.
no code implementations • 17 May 2023 • Weitao Chen, Hongbin Xu, Zhipeng Zhou, Yang Liu, Baigui Sun, Wenxiong Kang, Xuansong Xie
The Residual Depth-Aware Cost Transformer(RDACT) is proposed to aggregate long-range features on cost volume via self-attention mechanisms along the depth and spatial dimensions.
no code implementations • 12 May 2023 • Jian Zhao, Jianan Li, Lei Jin, Jiaming Chu, Zhihao Zhang, Jun Wang, Jiangqiang Xia, Kai Wang, Yang Liu, Sadaf Gulshad, Jiaojiao Zhao, Tianyang Xu, XueFeng Zhu, Shihan Liu, Zheng Zhu, Guibo Zhu, Zechao Li, Zheng Wang, Baigui Sun, Yandong Guo, Shin ichi Satoh, Junliang Xing, Jane Shen Shengmei
Second, we set up two tracks for the first time, i. e., Anti-UAV Tracking and Anti-UAV Detection & Tracking.
1 code implementation • 18 Apr 2023 • Zisheng Chen, Hongbin Xu, Weitao Chen, Zhipeng Zhou, Haihong Xiao, Baigui Sun, Xuansong Xie, Wenxiong Kang
Semantic segmentation of point clouds usually requires exhausting efforts of human annotations, hence it attracts wide attention to the challenging topic of learning from unlabeled or weaker forms of annotations.
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.
no code implementations • CVPR 2023 • Yang Liu, Zhipeng Zhou, Baigui Sun
To cope with two aforementioned issues, we propose a Clustering-based Optimal Transport (COT) algorithm, which formulates the alignment procedure as an Optimal Transport problem and constructs a mapping between clustering centers in the source and target domain via an end-to-end manner.
1 code implementation • ICCV 2023 • Zisheng Chen, Hongbin Xu, Weitao Chen, Zhipeng Zhou, Haihong Xiao, Baigui Sun, Xuansong Xie, Wenxiong Kang
Semantic segmentation of point clouds usually requires exhausting efforts of human annotations, hence it attracts wide attention to a challenging topic of learning from unlabeled or weaker form of annotations.
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.
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.
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.
no code implementations • 24 Jul 2022 • Hongbin Xu, Weitao Chen, Yang Liu, Zhipeng Zhou, Haihong Xiao, Baigui Sun, Xuansong Xie, Wenxiong Kang
For further troublesome case that the basic assumption is conflicted in MVS data, we propose a novel style consistency loss to alleviate the negative effect caused by the distribution gap.
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
1 code implementation • 3 Dec 2021 • Shiming Chen, Ziming Hong, Yang Liu, Guo-Sen Xie, Baigui Sun, Hao Li, Qinmu Peng, Ke Lu, Xinge You
Although some attention-based models have attempted to learn such region features in a single image, the transferability and discriminative attribute localization of visual features are typically neglected.
2 code implementations • NeurIPS 2021 • Shiming Chen, Guo-Sen Xie, Yang Liu, Qinmu Peng, Baigui Sun, Hao Li, Xinge You, Ling Shao
Specifically, HSVA aligns the semantic and visual domains by adopting a hierarchical two-step adaptation, i. e., structure adaptation and distribution adaptation.
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.
1 code implementation • ICCV 2021 • Hongbin Xu, Zhipeng Zhou, Yali Wang, Wenxiong Kang, Baigui Sun, Hao Li, Yu Qiao
Specially, the limitations can be categorized into two types: ambiguious supervision in foreground and invalid supervision in background.
1 code implementation • CVPR 2022 • Kai Wang, Shuo Wang, Panpan Zhang, Zhipeng Zhou, Zheng Zhu, Xiaobo Wang, Xiaojiang Peng, Baigui Sun, Hao Li, Yang You
This method adopts Dynamic Class Pool (DCP) for storing and updating the identities features dynamically, which could be regarded as a substitute for the FC layer.
Ranked #1 on Face Verification on IJB-C (training dataset metric)
no code implementations • 23 Apr 2021 • Jinxing Ye, Xioajiang Peng, Baigui Sun, Kai Wang, Xiuyu Sun, Hao Li, Hanqing Wu
In this paper, we repurpose the well-known Transformer and introduce a Face Transformer for supervised face clustering.
2 code implementations • CVPR 2022 • Yang Liu, Fei Wang, Jiankang Deng, Zhipeng Zhou, Baigui Sun, Hao Li
As a result, practical solutions on label assignment, scale-level data augmentation, and reducing false alarms are necessary for advancing face detectors.
Ranked #13 on Face Detection on WIDER Face (Easy)
no code implementations • 18 Dec 2020 • Kai Wang, Yuxin Gu, Xiaojiang Peng, Panpan Zhang, Baigui Sun, Hao Li
The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which pose an evident challenge for adapting the FER model trained on one dataset to another one.
Facial Expression Recognition Facial Expression Recognition (FER)
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)
no code implementations • 19 May 2018 • Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun, Hao Li
Hence, we propose to learn the model and the adversarial distribution simultaneously with the stochastic algorithm for efficiency.
no code implementations • 20 Sep 2016 • Junxuan Chen, Baigui Sun, Hao Li, Hongtao Lu, Xian-Sheng Hua
Click through rate (CTR) prediction of image ads is the core task of online display advertising systems, and logistic regression (LR) has been frequently applied as the prediction model.