no code implementations • 19 Nov 2023 • JIA YU, Lichao Zhang, Zijie Chen, Fayu Pan, Miaomiao Wen, Yuming Yan, Fangsheng Weng, Shuai Zhang, Lili Pan, Zhenzhong Lan
Moreover, to foster standardization in the T2I-based fashion design field, we propose a new benchmark comprising multiple datasets for evaluating the performance of fashion design models.
1 code implementation • 12 Oct 2023 • Zijie Chen, Lichao Zhang, Fangsheng Weng, Lili Pan, Zhenzhong Lan
Despite significant progress in the field, it is still challenging to create personalized visual representations that align closely with the desires and preferences of individual users.
1 code implementation • 26 Jan 2023 • Linfeng Xu, Qingbo Wu, Lili Pan, Fanman Meng, Hongliang Li, Chiyuan He, Hanxin Wang, Shaoxu Cheng, Yu Dai
However, the deficiency of related dataset hinders the development of multi-modal deep learning for egocentric activity recognition.
no code implementations • CVPR 2023 • Benliu Qiu, Hongliang Li, Haitao Wen, Heqian Qiu, Lanxiao Wang, Fanman Meng, Qingbo Wu, Lili Pan
We place continual learning into a causal framework, based on which we find the task-induced bias is reduced naturally by two underlying mechanisms in task and domain incremental learning.
1 code implementation • 13 Dec 2021 • Lili Pan, Mingming Meng, Yazhou Ren, Yali Zheng, Zenglin Xu
To answer this question, this paper proposes a new SPL method: easy and underrepresented examples first, for learning DDMs.
1 code implementation • 20 Jul 2021 • Xu Luo, Yuxuan Chen, Liangjian Wen, Lili Pan, Zenglin Xu
The goal of few-shot classification is to classify new categories with few labeled examples within each class.
1 code implementation • 28 Mar 2021 • Jie Xu, Yazhou Ren, Huayi Tang, Zhimeng Yang, Lili Pan, Yang Yang, Xiaorong Pu
To leverage the multi-view complementary information, we concatenate all views' embedded features to form the global features, which can overcome the negative impact of some views' unclear clustering structures.
no code implementations • 5 Mar 2021 • Lili Pan, Peijun Tang, Zhiyong Chen, Zenglin Xu
Disentanglement is defined as the problem of learninga representation that can separate the distinct, informativefactors of variations of data.
no code implementations • 1 Jan 2021 • Xu Luo, Yuxuan Chen, Liangjian Wen, Lili Pan, Zenglin Xu
Few-shot learning aims to recognize new classes with few annotated instances within each category.
1 code implementation • 26 Jul 2020 • Jie Xu, Yazhou Ren, Guofeng Li, Lili Pan, Ce Zhu, Zenglin Xu
Firstly, the embedded representations of multiple views are learned individually by deep autoencoders.
no code implementations • ECCV 2020 • Lili Pan, Shijie Ai, Yazhou Ren, Zenglin Xu
Deep discriminative models (e. g. deep regression forests, deep neural decision forests) have achieved remarkable success recently to solve problems such as facial age estimation and head pose estimation.
no code implementations • 8 Oct 2019 • Shijie Ai, Lili Pan, Yazhou Ren
Facial age estimation is an important and challenging problem in computer vision.
1 code implementation • Neurocomputing 2019 • Yazhou Ren, Kangrong Hu, Xinyi Dai, Lili Pan, Steven C. H. Hoi, Zenglin Xu
Deep embedded clustering (DEC) is one of the state-of-the-art deep clustering methods.
no code implementations • 17 Dec 2018 • Lili Pan, Shen Cheng, Jian Liu, Yazhou Ren, Zenglin Xu
We study the problem of multimodal generative modelling of images based on generative adversarial networks (GANs).