no code implementations • 18 Mar 2024 • Yi Wu, Ziqiang Li, Heliang Zheng, Chaoyue Wang, Bin Li
Drawing on recent advancements in diffusion models for text-to-image generation, identity-preserved personalization has made significant progress in accurately capturing specific identities with just a single reference image.
no code implementations • 4 Feb 2024 • Xin Jin, Bohan Li, Baao Xie, Wenyao Zhang, Jinming Liu, Ziqiang Li, Tao Yang, Wenjun Zeng
Representation disentanglement may help AI fundamentally understand the real world and thus benefit both discrimination and generation tasks.
no code implementations • 30 Jan 2024 • Shuhan Zheng, Ziqiang Li, Kantaro Fujiwara, Gouhei Tanaka
Dynamical behaviors of complex interacting systems, including brain activities, financial price movements, and physical collective phenomena, are associated with underlying interactions between the system's components.
no code implementations • 8 Jan 2024 • Long Deng, Ziqiang Li, Bingxin Zhou, Zhongming Chen, Ao Li, Yongxin Ge
Although few-shot action recognition based on metric learning paradigm has achieved significant success, it fails to address the following issues: (1) inadequate action relation modeling and underutilization of multi-modal information; (2) challenges in handling video matching problems with different lengths and speeds, and video matching problems with misalignment of video sub-actions.
no code implementations • 23 Nov 2023 • Yueqi Zeng, Ziqiang Li, Pengfei Xia, Lei Liu, Bin Li
With the boom in the natural language processing (NLP) field these years, backdoor attacks pose immense threats against deep neural network models.
no code implementations • 14 Nov 2023 • Ziqiang Li, Chaoyue Wang, Xue Rui, Chao Xue, Jiaxu Leng, Bin Li
Few-shot image generation aims to train generative models using a small number of training images.
no code implementations • 15 Oct 2023 • Ziqiang Li, Pengfei Xia, Hong Sun, Yueqi Zeng, Wei zhang, Bin Li
In this study, we focus on improving the poisoning efficiency of backdoor attacks from the sample selection perspective.
no code implementations • 3 Jul 2023 • Ziqiang Li, Kantaro Fujiwara, Gouhei Tanaka
The Dissemination Process Classification (DPC) is a popular application of temporal graph classification.
no code implementations • 14 Jun 2023 • Ziqiang Li, Hong Sun, Pengfei Xia, Beihao Xia, Xue Rui, Wei zhang, Qinglang Guo, Bin Li
This paper presents a Proxy attack-Free Strategy (PFS) designed to identify efficient poisoning samples based on individual similarity and ensemble diversity, effectively addressing the mentioned concern.
1 code implementation • 14 Jun 2023 • Ziqiang Li, Hong Sun, Pengfei Xia, Heng Li, Beihao Xia, Yi Wu, Bin Li
However, existing backdoor attack methods make unrealistic assumptions, assuming that all training data comes from a single source and that attackers have full access to the training data.
1 code implementation • 16 Mar 2023 • Jia Li, Yin Chen, Xuesong Zhang, Jiantao Nie, Ziqiang Li, Yangchen Yu, Yan Zhang, Richang Hong, Meng Wang
In this paper, we present our advanced solutions to the two sub-challenges of Affective Behavior Analysis in the wild (ABAW) 2023: the Emotional Reaction Intensity (ERI) Estimation Challenge and Expression (Expr) Classification Challenge.
1 code implementation • 18 Jul 2022 • Ziqiang Li, Chaoyue Wang, Heliang Zheng, Jing Zhang, Bin Li
Since data augmentation strategies have largely alleviated the training instability, how to further improve the generative performance of DE-GANs becomes a hotspot.
no code implementations • 14 Jul 2022 • Ziqiang Li, Yongxin Ge, Jiaruo Yu, Zhongming Chen
With video-level labels, weakly supervised temporal action localization (WTAL) applies a localization-by-classification paradigm to detect and classify the action in untrimmed videos.
Classification Weakly-supervised Temporal Action Localization +1
1 code implementation • 22 Apr 2022 • Pengfei Xia, Ziqiang Li, Wei zhang, Bin Li
Recent studies have proven that deep neural networks are vulnerable to backdoor attacks.
no code implementations • 18 Apr 2022 • Ziqiang Li, Beihao Xia, Jing Zhang, Chaoyue Wang, Bin Li
Generative Adversarial Networks (GANs) have achieved remarkable achievements in image synthesis.
no code implementations • 9 Nov 2021 • Pengfei Xia, Ziqiang Li, Bin Li
The most common solution for this is to compute an approximate risk by replacing the 0-1 loss with a surrogate one.
1 code implementation • 9 Nov 2021 • Pengfei Xia, Hongjing Niu, Ziqiang Li, Bin Li
Then, ML-MMDR, a difference reduction method that adds multi-level MMD regularization into the loss, is proposed, and its effectiveness is testified on three typical difference-based defense methods.
2 code implementations • 20 Mar 2021 • Ziqiang Li, Pengfei Xia, Xue Rui, Bin Li
Generative Adversarial Networks (GANs) have the ability to generate images that are visually indistinguishable from real images.
1 code implementation • 19 Aug 2020 • Ziqiang Li, Pengfei Xia, Rentuo Tao, Hongjing Niu, Bin Li
Quite a number of methods have been proposed to stabilize the training of GANs, the focuses of which were respectively put on the loss functions, regularization and normalization technologies, training algorithms, and model architectures.
1 code implementation • 19 Aug 2020 • Ziqiang Li, Muhammad Usman, Rentuo Tao, Pengfei Xia, Chaoyue Wang, Huanhuan Chen, Bin Li
Although a handful number of regularization and normalization methods have been proposed for GANs, to the best of our knowledge, there exists no comprehensive survey that primarily focuses on objectives and development of these methods, apart from some in-comprehensive and limited scope studies.
no code implementations • 2 Jul 2020 • Ziqiang Li, Hong Pan, Yaping Zhu, A. K. Qin
Position information is explicitly encoded into the network to enhance the capabilities of deformation.
no code implementations • 23 May 2020 • Ziqiang Li, Rentuo Tao, Hongjing Niu, Bin Li
Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution and drug discovery, etc., by now, the inner process of GANs is far from been understood.
1 code implementation • 15 Jul 2019 • Ziqiang Li, Rentuo Tao, Qianrun Wu, Bin Li
Automatic medical image segmentation has wide applications for disease diagnosing.