1 citations · 2 across the 6 of their papers we have counts for
8 papers
Semantic Visual Anomaly Detection and Reasoning in AI-Generated Images
Chuangchuang Tan, Xiang Ming, Jinglu Wang +5
The rapid advancement of AI-generated content (AIGC) has enabled the synthesis of visually convincing images; however, many such outputs exhibit subtle \textbf{semantic anomalies},…
ForenX: Towards Explainable AI-Generated Image Detection with Multimodal Large Language Models
Chuangchuang Tan, Jinglu Wang, Xiang Ming +4
Advances in generative models have led to AI-generated images visually indistinguishable from authentic ones. Despite numerous studies on detecting AI-generated images with classif…
Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks
Manyi Li, Renshuai Tao, Yufan Liu +5
With the rapid advancement of deep learning, particularly through generative adversarial networks (GANs) and diffusion models (DMs), AI-generated images, or ``deepfakes", have beco…
DCI: Dual-Conditional Inversion for Boosting Diffusion-Based Image Editing
Zixiang Li, Haoyu Wang, Wei Wang +3
Diffusion models have achieved remarkable success in image generation and editing tasks. Inversion within these models aims to recover the latent noise representation for a real or…
Unsupervised Region-Based Image Editing of Denoising Diffusion Models
Zixiang Li, Yue Song, Renshuai Tao +3
Although diffusion models have achieved remarkable success in the field of image generation, their latent space remains under-explored. Current methods for identifying semantics wi…
Behavior Backdoor for Deep Learning Models
Jiakai Wang, Pengfei Zhang, Renshuai Tao +5
The various post-processing methods for deep-learning-based models, such as quantification, pruning, and fine-tuning, play an increasingly important role in artificial intelligence…