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20242026
most citedDetecting Multimedia Generated by Large AI Models: A Survey

5 citations · 14 across the 22 of their papers we have counts for

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11 papers · 1 filter

cs.SD2024★ 1 cited

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…

cs.AI2024

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…

eess.IV2024

Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation

Xin Wang, Xiaoyu Liu, Peng Huang +3

Medical Image Foundation Models have proven to be powerful tools for mask prediction across various datasets. However, accurately assessing the uncertainty of their predictions rem…

cs.CV2024

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…

eess.IV2024★ 1 cited

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…

cs.CV2024★ 2 cited

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…

cs.CV2024

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…

eess.IV2024

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,…

cs.CV2024

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…

cs.MM2024★ 5 cited

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…

cs.IR2024★ 1 cited

Uncertainty-Aware Explainable Recommendation with Large Language Models

Yicui Peng, Hao Chen, Chingsheng Lin +7

Providing explanations within the recommendation system would boost user satisfaction and foster trust, especially by elaborating on the reasons for selecting recommended items tai…