11 citations · 13 across the 10 of their papers we have counts for
10 papers
Progressively Exploring and Exploiting Inference Data to Break Fine-Grained Classification Barrier
Li-Jun Zhao, Si-Yuan Zhang, Zhen-Duo Chen +2
Current fine-grained classification research primarily focuses on fine-grained feature learning. However, in real-world scenarios, fine-grained data annotation is challenging, and…
EVC-MF: End-to-end Video Captioning Network with Multi-scale Features
Tian-Zi Niu, Zhen-Duo Chen, Xin Luo +1
Conventional approaches for video captioning leverage a variety of offline-extracted features to generate captions. Despite the availability of various offline-feature-extractors t…
Bias Mitigating Few-Shot Class-Incremental Learning
Li-Jun Zhao, Zhen-Duo Chen, Zi-Chao Zhang +2
Few-shot class-incremental learning (FSCIL) aims at recognizing novel classes continually with limited novel class samples. A mainstream baseline for FSCIL is first to train the wh…
Federated Class-Incremental Learning with Prompting
Xin Luo, Fang-Yi Liang, Jiale Liu +3
As Web technology continues to develop, it has become increasingly common to use data stored on different clients. At the same time, federated learning has received widespread atte…
FedVMR: A New Federated Learning method for Video Moment Retrieval
Yan Wang, Xin Luo, Zhen-Duo Chen +3
Despite the great success achieved, existing video moment retrieval (VMR) methods are developed under the assumption that data are centralizedly stored. However, in real-world appl…
Prototype-Based Layered Federated Cross-Modal Hashing
Jiale Liu, Yu-Wei Zhan, Xin Luo +3
Recently, deep cross-modal hashing has gained increasing attention. However, in many practical cases, data are distributed and cannot be collected due to privacy concerns, which gr…
Three-Stream Joint Network for Zero-Shot Sketch-Based Image Retrieval
Yu-Wei Zhan, Xin Luo, Yongxin Wang +2
The Zero-Shot Sketch-based Image Retrieval (ZS-SBIR) is a challenging task because of the large domain gap between sketches and natural images as well as the semantic inconsistency…
ViT-FOD: A Vision Transformer based Fine-grained Object Discriminator
Zi-Chao Zhang, Zhen-Duo Chen, Yongxin Wang +2
Recently, several Vision Transformer (ViT) based methods have been proposed for Fine-Grained Visual Classification (FGVC).These methods significantly surpass existing CNN-based one…
Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data
Xiao-Ming Wu, Xin Luo, Yu-Wei Zhan +3
With the vigorous development of multimedia equipment and applications, efficient retrieval of large-scale multi-modal data has become a trendy research topic. Thereinto, hashing h…
Weakly-Supervised Online Hashing
Yu-Wei Zhan, Xin Luo, Yu Sun +3
With the rapid development of social websites, recent years have witnessed an explosive growth of social images with user-provided tags which continuously arrive in a streaming fas…