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CoCoDiff: Correspondence-Consistent Diffusion Model for Fine-grained Style Transfer
Wenbo Nie, Zixiang Li, Renshuai Tao +3
Transferring visual style between images while preserving semantic correspondence between similar objects remains a central challenge in computer vision. While existing methods hav…
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…
BGM: Background Mixup for X-ray Prohibited Items Detection
Weizhe Liu, Renshuai Tao, Hongguang Zhu +3
Current data-driven approaches for X-ray prohibited items detection remain under-explored, particularly in the design of effective data augmentations. Existing natural image augmen…
Dual-view X-ray Detection: Can AI Detect Prohibited Items from Dual-view X-ray Images like Humans?
Renshuai Tao, Haoyu Wang, Yuzhe Guo +5
To detect prohibited items in challenging categories, human inspectors typically rely on images from two distinct views (vertical and side). Can AI detect prohibited items from dua…