8 citations · 26 across the 9 of their papers we have counts for
9 papers
Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection
Jieren Deng, Haojian Zhang, Kun Ding +3
This paper presents Incremental Vision-Language Object Detection (IVLOD), a novel learning task designed to incrementally adapt pre-trained Vision-Language Object Detection Models…
GBSD: Generative Bokeh with Stage Diffusion
Jieren Deng, Xin Zhou, Hao Tian +2
The bokeh effect is an artistic technique that blurs out-of-focus areas in a photograph and has gained interest due to recent developments in text-to-image synthesis and the ubiqui…
Smooth and Stepwise Self-Distillation for Object Detection
Jieren Deng, Xin Zhou, Hao Tian +2
Distilling the structured information captured in feature maps has contributed to improved results for object detection tasks, but requires careful selection of baseline architectu…
Incremental Prototype Tuning for Class Incremental Learning
Jieren Deng, Jianhua Hu, Haojian Zhang +1
Class incremental learning(CIL) has attracted much attention, but most existing related works focus on fine-tuning the entire representation model, which inevitably results in much…
A Secure and Efficient Federated Learning Framework for NLP
Jieren Deng, Chenghong Wang, Xianrui Meng +7
In this work, we consider the problem of designing secure and efficient federated learning (FL) frameworks. Existing solutions either involve a trusted aggregator or require heavyw…
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices
Sahidul Islam, Jieren Deng, Shanglin Zhou +3
Energy harvesting (EH) IoT devices that operate intermittently without batteries, coupled with advances in deep neural networks (DNNs), have opened up new opportunities for enablin…
TAG: Gradient Attack on Transformer-based Language Models
Jieren Deng, Yijue Wang, Ji Li +4
Although federated learning has increasingly gained attention in terms of effectively utilizing local devices for data privacy enhancement, recent studies show that publicly shared…
SAPAG: A Self-Adaptive Privacy Attack From Gradients
Yijue Wang, Jieren Deng, Dan Guo +5
Distributed learning such as federated learning or collaborative learning enables model training on decentralized data from users and only collects local gradients, where data is p…
ESMFL: Efficient and Secure Models for Federated Learning
Sheng Lin, Chenghong Wang, Hongjia Li +3
Nowadays, Deep Neural Networks are widely applied to various domains. However, massive data collection required for deep neural network reveals the potential privacy issues and als…