no code implementations • 14 Aug 2024 • Zhonglin Chen, Anyu Geng, Jianan Jiang, Jiwu Lu, Di wu
The proposed FFAFPM can enrich semantic information, and enhance the fusion of shallow feature and deep feature, thus false positive results have been significantly reduced.
no code implementations • 17 Jun 2024 • Jianan Jiang, Di wu, Zhilin Jiang, Weiren Yu
Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) aims to minimize the distance between sketches and corresponding images in the embedding space.
1 code implementation • 13 Mar 2024 • Jianan Jiang, Xinglin Li, Weiren Yu, Di wu
In the realm of fashion design, sketches serve as the canvas for expressing an artist's distinctive drawing style and creative vision, capturing intricate details like stroke variations and texture nuances.
no code implementations • 3 Dec 2020 • Zhenpeng Li, Jianan Jiang, Yuhong Guo, Tiantian Tang, Chengxiang Zhuo, Jieping Ye
In the proposed model, we design a data imputation module to fill the missing feature values based on the partial observations in the target domain, while aligning the two domains via deep adversarial adaption.
1 code implementation • 8 Jun 2020 • Jianan Jiang, Zhenpeng Li, Yuhong Guo, Jieping Ye
The TMHFS method extends the Meta-Confidence Transduction (MCT) and Dense Feature-Matching Networks (DFMN) method [2] by introducing a new prediction head, i. e, an instance-wise global classification network based on semantic information, after the common feature embedding network.
no code implementations • 18 May 2020 • Bingyu Liu, Zhen Zhao, Zhenpeng Li, Jianan Jiang, Yuhong Guo, Jieping Ye
In this paper, we propose a feature transformation ensemble model with batch spectral regularization for the Cross-domain few-shot learning (CD-FSL) challenge.
no code implementations • 2 Jul 2019 • Qing Song, Yao Guo, Jianan Jiang, Chun Liu, Mengjie Hu
Railway transportation is the artery of China's national economy and plays an important role in the development of today's society.