6 citations · 18 across the 15 of their papers we have counts for
15 papers
PX2Tooth: Reconstructing the 3D Point Cloud Teeth from a Single Panoramic X-ray
Wen Ma, Huikai Wu, Zikai Xiao +3
Reconstructing the 3D anatomical structures of the oral cavity, which originally reside in the cone-beam CT (CBCT), from a single 2D Panoramic X-ray(PX) remains a critical yet chal…
Large Language Model Bias Mitigation from the Perspective of Knowledge Editing
Ruizhe Chen, Yichen Li, Zikai Xiao +1
Existing debiasing methods inevitably make unreasonable or undesired predictions as they are designated and evaluated to achieve parity across different social groups but leave asi…
Learnable Privacy Neurons Localization in Language Models
Ruizhe Chen, Tianxiang Hu, Yang Feng +1
Concerns regarding Large Language Models (LLMs) to memorize and disclose private information, particularly Personally Identifiable Information (PII), become prominent within the co…
FAIntbench: A Holistic and Precise Benchmark for Bias Evaluation in Text-to-Image Models
Hanjun Luo, Ziye Deng, Ruizhe Chen +1
The rapid development and reduced barriers to entry for Text-to-Image (T2I) models have raised concerns about the biases in their outputs, but existing research lacks a holistic de…
MedThink: Explaining Medical Visual Question Answering via Multimodal Decision-Making Rationale
Xiaotang Gai, Chenyi Zhou, Jiaxiang Liu +3
Medical Visual Question Answering (MedVQA), which offers language responses to image-based medical inquiries, represents a challenging task and significant advancement in healthcar…
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu +6
Federated Long-Tailed Learning (Fed-LT), a paradigm wherein data collected from decentralized local clients manifests a globally prevalent long-tailed distribution, has garnered co…
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer
Zikai Xiao, Zihan Chen, Songshang Liu +7
Data privacy and long-tailed distribution are the norms rather than the exception in many real-world tasks. This paper investigates a federated long-tailed learning (Fed-LT) task i…
TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer
Huimin Xiong, Kunle Li, Kaiyuan Tan +6
Optical Intraoral Scanners (IOS) are widely used in digital dentistry to provide detailed 3D information of dental crowns and the gingiva. Accurate 3D tooth segmentation in IOSs is…
Fast Model Debias with Machine Unlearning
Ruizhe Chen, Jianfei Yang, Huimin Xiong +7
Recent discoveries have revealed that deep neural networks might behave in a biased manner in many real-world scenarios. For instance, deep networks trained on a large-scale face r…
Robustness-Guided Image Synthesis for Data-Free Quantization
Jianhong Bai, Yuchen Yang, Huanpeng Chu +7
Quantization has emerged as a promising direction for model compression. Recently, data-free quantization has been widely studied as a promising method to avoid privacy concerns, w…
Towards Distribution-Agnostic Generalized Category Discovery
Jianhong Bai, Zuozhu Liu, Hualiang Wang +7
Data imbalance and open-ended distribution are two intrinsic characteristics of the real visual world. Though encouraging progress has been made in tackling each challenge separate…
3D-U-SAM Network For Few-shot Tooth Segmentation in CBCT Images
Yifu Zhang, Zuozhu Liu, Yang Feng +1
Accurate representation of tooth position is extremely important in treatment. 3D dental image segmentation is a widely used method, however labelled 3D dental datasets are a scarc…
ToothSegNet: Image Degradation meets Tooth Segmentation in CBCT Images
Jiaxiang Liu, Tianxiang Hu, Yang Feng +2
In computer-assisted orthodontics, three-dimensional tooth models are required for many medical treatments. Tooth segmentation from cone-beam computed tomography (CBCT) images is a…
TFormer: 3D Tooth Segmentation in Mesh Scans with Geometry Guided Transformer
Huimin Xiong, Kunle Li, Kaiyuan Tan +4
Optical Intra-oral Scanners (IOS) are widely used in digital dentistry, providing 3-Dimensional (3D) and high-resolution geometrical information of dental crowns and the gingiva. A…
AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications
Jin Hao, Jiaxiang Liu, Jin Li +17
A critical step in virtual dental treatment planning is to accurately delineate all tooth-bone structures from CBCT with high fidelity and accurate anatomical information. Previous…