5 citations · 11 across the 14 of their papers we have counts for
14 papers
SynthGuard: An Open Platform for Detecting AI-Generated Multimedia with Multimodal LLMs
Shail Desai, Aditya Pawar, Li Lin +2
Artificial Intelligence (AI) has made it possible for anyone to create images, audio, and video with unprecedented ease, enriching education, communication, and creative expression…
Rethinking Individual Fairness in Deepfake Detection
Aryana Hou, Li Lin, Justin Li +1
Generative AI models have substantially improved the realism of synthetic media, yet their misuse through sophisticated DeepFakes poses significant risks. Despite recent advances i…
Preserving AUC Fairness in Learning with Noisy Protected Groups
Mingyang Wu, Li Lin, Wenbin Zhang +3
The Area Under the ROC Curve (AUC) is a key metric for classification, especially under class imbalance, with growing research focus on optimizing AUC over accuracy in applications…
Robust AI-Generated Face Detection with Imbalanced Data
Yamini Sri Krubha, Aryana Hou, Braden Vester +4
Deepfakes, created using advanced AI techniques such as Variational Autoencoder and Generative Adversarial Networks, have evolved from research and entertainment applications into…
Improving Generalization for AI-Synthesized Voice Detection
Hainan Ren, Li Lin, Chun-Hao Liu +2
AI-synthesized voice technology has the potential to create realistic human voices for beneficial applications, but it can also be misused for malicious purposes. While existing AI…
An Uncertainty-Aware Generalization Framework for Cardiovascular Image Segmentation
Ting Yu Tsai, Liangqiao Gui, Yineng Chen +8
Deep learning models have achieved significant success in segmenting cardiovascular structures, but there is a growing need to improve their generalization and robustness. Current…
AI-Face: A Million-Scale Demographically Annotated AI-Generated Face Dataset and Fairness Benchmark
Li Lin, Santosh, Mingyang Wu +2
AI-generated faces have enriched human life, such as entertainment, education, and art. However, they also pose misuse risks. Therefore, detecting AI-generated faces becomes crucia…
Fast Diffeomorphic Image Registration using Patch based Fully Convolutional Networks
Jiong Wu, Shuang Zhou, Li Lin +2
Diffeomorphic image registration is a fundamental step in medical image analysis, owing to its capability to ensure the invertibility of transformations and preservation of topolog…
UU-Mamba: Uncertainty-aware U-Mamba for Cardiac Image Segmentation
Ting Yu Tsai, Li Lin, Shu Hu +3
Biomedical image segmentation is critical for accurate identification and analysis of anatomical structures in medical imaging, particularly in cardiac MRI. Manual segmentation is…
Robust CLIP-Based Detector for Exposing Diffusion Model-Generated Images
Santosh, Li Lin, Irene Amerini +2
Diffusion models (DMs) have revolutionized image generation, producing high-quality images with applications spanning various fields. However, their ability to create hyper-realist…
Robust Light-Weight Facial Affective Behavior Recognition with CLIP
Li Lin, Sarah Papabathini, Xin Wang +1
Human affective behavior analysis aims to delve into human expressions and behaviors to deepen our understanding of human emotions. Basic expression categories (EXPR) and Action Un…
Robust COVID-19 Detection in CT Images with CLIP
Li Lin, Yamini Sri Krubha, Zhenhuan Yang +5
In the realm of medical imaging, particularly for COVID-19 detection, deep learning models face substantial challenges such as the necessity for extensive computational resources,…
Preserving Fairness Generalization in Deepfake Detection
Li Lin, Xinan He, Yan Ju +3
Although effective deepfake detection models have been developed in recent years, recent studies have revealed that these models can result in unfair performance disparities among…
Detecting Multimedia Generated by Large AI Models: A Survey
Li Lin, Neeraj Gupta, Yue Zhang +7
The rapid advancement of Large AI Models (LAIMs), particularly diffusion models and large language models, has marked a new era where AI-generated multimedia is increasingly integr…