20 citations · 179 across the 97 of their papers we have counts for
17 papers · 2 filters
HMGIE: Hierarchical and Multi-Grained Inconsistency Evaluation for Vision-Language Data Cleansing
Zihao Zhu, Hongbao Zhang, Guanzong Wu +2
Visual-textual inconsistency (VTI) evaluation plays a crucial role in cleansing vision-language data. Its main challenges stem from the high variety of image captioning datasets, w…
Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection
Delong Zhu, Yuezun Li, Baoyuan Wu +3
Face-swapping DeepFakes have become an escalating societal concern, attracting increasing attention in recent years. To counter this, we investigate a new proactive defense framewo…
Forensics Adapter: Unleashing CLIP for Generalizable Face Forgery Detection
Xinjie Cui, Yuezun Li, Delong Zhu +3
We describe Forensics Adapter, an adapter network designed to transform CLIP into an effective and generalizable face forgery detector. Although CLIP is highly versatile, adapting…
X2-DFD: A framework for eXplainable and eXtendable Deepfake Detection
Yize Chen, Zhiyuan Yan, Guangliang Cheng +3
This paper proposes X2-DFD, an eXplainable and eXtendable framework based on multimodal large-language models (MLLMs) for deepfake detection, consisting of three key stages. The fi…
Simple and Fast Distillation of Diffusion Models
Zhenyu Zhou, Defang Chen, Can Wang +2
Diffusion-based generative models have demonstrated their powerful performance across various tasks, but this comes at a cost of the slow sampling speed. To achieve both efficient…
Conditional Image Synthesis with Diffusion Models: A Survey
Zheyuan Zhan, Defang Chen, Jian-Ping Mei +5
Conditional image synthesis based on user-specified requirements is a key component in creating complex visual content. In recent years, diffusion-based generative modeling has bec…
Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach
Mian Zou, Baosheng Yu, Yibing Zhan +2
In recent years, the multimedia forensics and security community has seen remarkable progress in multitask learning for DeepFake (i.e., face forgery) detection. The prevailing appr…
Knowledge Distillation with Refined Logits
Wujie Sun, Defang Chen, Siwei Lyu +3
Recent research on knowledge distillation has increasingly focused on logit distillation because of its simplicity, effectiveness, and versatility in model compression. In this pap…
Dense Feature Interaction Network for Image Inpainting Localization
Ye Yao, Tingfeng Han, Shan Jia +1
Image inpainting, the process of filling in missing areas in an image, is a common image editing technique. Inpainting can be used to conceal or alter image contents in malicious m…
Vision-Language Model Based Handwriting Verification
Mihir Chauhan, Abhishek Satbhai, Mohammad Abuzar Hashemi +5
Handwriting Verification is a critical in document forensics. Deep learning based approaches often face skepticism from forensic document examiners due to their lack of explainabil…
ParallelEdits: Efficient Multi-object Image Editing
Mingzhen Huang, Jialing Cai, Shan Jia +2
Text-driven image synthesis has made significant advancements with the development of diffusion models, transforming how visual content is generated from text prompts. Despite thes…
Self-Supervised Learning Based Handwriting Verification
Mihir Chauhan, Mohammad Abuzar Hashemi, Abhishek Satbhai +5
We present SSL-HV: Self-Supervised Learning approaches applied to the task of Handwriting Verification. This task involves determining whether a given pair of handwritten images or…
Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
Mian Zou, Baosheng Yu, Yibing Zhan +2
In recent years, deep learning has greatly streamlined the process of manipulating photographic face images. Aware of the potential dangers, researchers have developed various tool…
Explicit Correlation Learning for Generalizable Cross-Modal Deepfake Detection
Cai Yu, Shan Jia, Xiaomeng Fu +6
With the rising prevalence of deepfakes, there is a growing interest in developing generalizable detection methods for various types of deepfakes. While effective in their specific…
Exposing Text-Image Inconsistency Using Diffusion Models
Mingzhen Huang, Shan Jia, Zhou Zhou +3
In the battle against widespread online misinformation, a growing problem is text-image inconsistency, where images are misleadingly paired with texts with different intent or mean…
Texture, Shape, Order, and Relation Matter: A New Transformer Design for Sequential DeepFake Detection
Yunfei Li, Yuezun Li, Baoyuan Wu +3
Sequential DeepFake detection is an emerging task that predicts the manipulation sequence in order. Existing methods typically formulate it as an image-to-sequence problem, employi…
Exposing Lip-syncing Deepfakes from Mouth Inconsistencies
Soumyya Kanti Datta, Shan Jia, Siwei Lyu
A lip-syncing deepfake is a digitally manipulated video in which a person's lip movements are created convincingly using AI models to match altered or entirely new audio. Lip-synci…