45 citations · 72 across the 39 of their papers we have counts for
13 papers · 1 filter
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients
Shangchao Su, Bin Li, Xiangyang Xue
With the increasing availability of Foundation Models, federated tuning has garnered attention in the field of federated learning, utilizing data and computation resources from mul…
One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
Mingzhao Yang, Shangchao Su, Bin Li +1
In recent years, One-shot Federated Learning methods based on Diffusion Models have garnered increasing attention due to their remarkable performance. However, most of these method…
Orientation-Independent Chinese Text Recognition in Scene Images
Haiyang Yu, Xiaocong Wang, Bin Li +1
Scene text recognition (STR) has attracted much attention due to its broad applications. The previous works pay more attention to dealing with the recognition of Latin text images…
Rethinking Person Re-identification from a Projection-on-Prototypes Perspective
Qizao Wang, Xuelin Qian, Bin Li +2
Person Re-IDentification (Re-ID) as a retrieval task, has achieved tremendous development over the past decade. Existing state-of-the-art methods follow an analogous framework to f…
Exploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification
Qizao Wang, Xuelin Qian, Bin Li +2
Cloth-changing person Re-IDentification (Re-ID) is a particularly challenging task, suffering from two limitations of inferior discriminative features and limited training samples.…
Abstracting Concept-Changing Rules for Solving Raven's Progressive Matrix Problems
Fan Shi, Bin Li, Xiangyang Xue
The abstract visual reasoning ability in human intelligence benefits discovering underlying rules in the novel environment. Raven's Progressive Matrix (RPM) is a classic test to re…
OCTScenes: A Versatile Real-World Dataset of Tabletop Scenes for Object-Centric Learning
Yinxuan Huang, Tonglin Chen, Zhimeng Shen +3
Humans possess the cognitive ability to comprehend scenes in a compositional manner. To empower AI systems with similar capabilities, object-centric learning aims to acquire repres…
Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis
Zhiyu Jin, Xuli Shen, Bin Li +1
Diffusion models (DMs) have recently gained attention with state-of-the-art performance in text-to-image synthesis. Abiding by the tradition in deep learning, DMs are trained and e…
Collaborative Chinese Text Recognition with Personalized Federated Learning
Shangchao Su, Haiyang Yu, Bin Li +1
In Chinese text recognition, to compensate for the insufficient local data and improve the performance of local few-shot character recognition, it is often necessary for one organi…
Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model
Mingzhao Yang, Shangchao Su, Bin Li +1
Recently, semi-supervised federated learning (semi-FL) has been proposed to handle the commonly seen real-world scenarios with labeled data on the server and unlabeled data on the…
GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection
Xinxin Hu, Haotian Chen, Junjie Zhang +5
Along with the rapid evolution of mobile communication technologies, such as 5G, there has been a drastically increase in telecom fraud, which significantly dissipates individual f…
Cost Sensitive GNN-based Imbalanced Learning for Mobile Social Network Fraud Detection
Xinxin Hu, Haotian Chen, Hongchang Chen +5
With the rapid development of mobile networks, the people's social contacts have been considerably facilitated. However, the rise of mobile social network fraud upon those networks…
Weakly-Supervised Text Instance Segmentation
Xinyan Zu, Haiyang Yu, Bin Li +1
Text segmentation is a challenging vision task with many downstream applications. Current text segmentation methods require pixel-level annotations, which are expensive in the cost…