9 citations · 17 across the 7 of their papers we have counts for
7 papers
SteelDefectX: A Multi-Form Vision-Language Dataset and Benchmark for Steel Surface Defect Analysis
Shuxian Zhao, Jie Gui, Baosheng Yu +1
Steel surface defect analysis is critical for industrial quality control, yet existing benchmarks rely primarily on label-only annotations, limiting fine-grained semantic understan…
On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View
Tao Guo, Junxiao Wang, Fushuo Huo +4
Federated Learning (FL) enables training models across decentralized data silos while preserving client data privacy. Recent research has explored efficient methods for post-traini…
The Devil is in the Darkness: Diffusion-Based Nighttime Dehazing Anchored in Brightness Perception
Xiaofeng Cong, Yu-Xin Zhang, Haoran Wei +5
While nighttime image dehazing has been extensively studied, converting nighttime hazy images to daytime-equivalent brightness remains largely unaddressed. Existing methods face tw…
Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective
Jie Gui, Chengze Jiang, Minjing Dong +4
While adversarial training is an effective defense method against adversarial attacks, it notably increases the training cost. To this end, fast adversarial training (FAT) is prese…
A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning
Xiaofeng Cong, Yu Zhao, Jie Gui +2
Underwater image enhancement (UIE) presents a significant challenge within computer vision research. Despite the development of numerous UIE algorithms, a thorough and systematic r…
Federated Distillation: A Survey
Lin Li, Jianping Gou, Baosheng Yu +2
Federated Learning (FL) seeks to train a model collaboratively without sharing private training data from individual clients. Despite its promise, FL encounters challenges such as…
Deep Learning-Based Point Cloud Registration: A Comprehensive Survey and Taxonomy
Yu-Xin Zhang, Jie Gui, Baosheng Yu +4
Point cloud registration involves determining a rigid transformation to align a source point cloud with a target point cloud. This alignment is fundamental in applications such as…