1 code implementation • 10 Mar 2025 • Ruidong Chen, Honglin Guo, Lanjun Wang, Chenyu Zhang, Weizhi Nie, An-An Liu
Firstly, TRCE starts by erasing the malicious semantics implicitly embedded in textual prompts.
no code implementations • CVPR 2024 • Ruidong Chen, Lanjun Wang, Weizhi Nie, Yongdong Zhang, An-An Liu
Recent advancements in text-to-image technology have significantly advanced the field of image customization.
no code implementations • 30 Nov 2023 • Dan Song, Xinwei Fu, Ning Liu, Weizhi Nie, Wenhui Li, Lanjun Wang, You Yang, AnAn Liu
Consequently, this paper aims to improve the confidence with view selection and hierarchical prompts.
1 code implementation • CVPR 2024 • Jianhao Zeng, Dan Song, Weizhi Nie, Hongshuo Tian, Tongtong Wang, AnAn Liu
Generative Adversarial Networks (GANs) dominate the research field in image-based virtual try-on, but have not resolved problems such as unnatural deformation of garments and the blurry generation quality.
1 code implementation • 8 Nov 2023 • Dan Song, Xuanpu Zhang, Juan Zhou, Weizhi Nie, Ruofeng Tong, Mohan Kankanhalli, An-An Liu
Image-based virtual try-on aims to synthesize a naturally dressed person image with a clothing image, which revolutionizes online shopping and inspires related topics within image generation, showing both research significance and commercial potential.
no code implementations • 13 Sep 2023 • Yuting Su, Yichen Wei, Weizhi Nie, Sicheng Zhao, AnAn Liu
Specifically, we propose a dynamic temporal disentanglement model to infer the propagation of utterances and hidden variables, enabling the accumulation of emotion-related information throughout the conversation.
1 code implementation • 26 Aug 2023 • Qiang Li, Qiuyang Ma, Weizhi Nie, AnAn Liu
We employed a clustering method with varying constraint conditions, ranging from strict to loose, allowing for the generation of dependable labels for a subset of unlabeled data during the training phase.
no code implementations • 6 Aug 2023 • Rihao Chang, Yongtao Ma, Weizhi Nie, Jie Nie, An-An Liu
In modern industries, fault diagnosis has been widely applied with the goal of realizing predictive maintenance.
no code implementations • 3 Jun 2023 • Weizhi Nie, Yuhe Yu, Chen Zhang, Dan Song, Lina Zhao, Yunpeng Bai
Our method can also find key clinical indicators of important outcomes that can be used to improve treatment options.
1 code implementation • 2 Jun 2023 • Weizhi Nie, Chen Zhang, Dan Song, Lina Zhao, Yunpeng Bai, Keliang Xie, AnAn Liu
The chest X-ray is often utilized for diagnosing common thoracic diseases.
no code implementations • 28 May 2023 • Songxue Gao, Chuanqi Jiao, Ruidong Chen, Weijie Wang, Weizhi Nie
In this paper, we propose a novel approach to point cloud completion task called Point-PC, which uses a memory network to retrieve shape priors and designs a causal inference model to filter missing shape information as supplemental geometric information to aid point cloud completion.
no code implementations • 25 May 2023 • Weizhi Nie, Ruidong Chen, Weijie Wang, Bruno Lepri, Nicu Sebe
Meanwhile, to effectively integrate multi-modal prior knowledge into textual information, we adopt a novel multi-layer transformer structure to progressively fuse related shape and textual information, which can effectively compensate for the lack of structural information in the text and enhance the final performance of the 3D generation model.
no code implementations • 20 May 2023 • Weizhi Nie, Chen Zhang, Dan Song, Yunpeng Bai, Keliang Xie, AnAn Liu
The chest X-ray (CXR) is commonly employed to diagnose thoracic illnesses, but the challenge of achieving accurate automatic diagnosis through this method persists due to the complex relationship between pathology.
no code implementations • 20 May 2023 • Weizhi Nie, Chen Zhang, Dan Song, Lina Zhao, Yunpeng Bai, Keliang Xie, AnAn Liu
The chest X-ray (CXR) is one of the most common and easy-to-get medical tests used to diagnose common diseases of the chest.
no code implementations • 27 Oct 2022 • Rihao Chang, Yongtao Ma, Tong Hao, Weizhi Nie
To establish the knowledge graph, we employ geometric words as nodes, connecting them via shape categories and geometry attributes.
no code implementations • 10 Aug 2021 • Zan Gao, Hongwei Wei, Weili Guan, Weizhi Nie, Meng Liu, Meng Wang
To solve these issues, in this work, a novel multigranular visual-semantic embedding algorithm (MVSE) is proposed for cloth-changing person ReID, where visual semantic information and human attributes are embedded into the network, and the generalized features of human appearance can be well learned to effectively solve the problem of clothing changes.