Papers Image Manipulation Detection
“Image Manipulation Detection” 태그가 달린 논문 82편 · 필터 해제
Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization
Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for image manipulation detection and localization (IMDL). However, existin…
Image Manipulation LocalizationImage Manipulation DetectionImage EditingMulti-axis Analysis of Image Manipulation Localization
Advanced image editing software enables easy creation of highly convincing image manipulations, which has been made even more accessible in recent years due to advances in generative AI. Manipulated images, while often h…
Image Manipulation LocalizationImage Manipulation DetectionImage EditingFRAME: Forensic Routing and Adaptive Multi-path Evidence Fusion for Image Manipulation Detection
The proliferation of sophisticated image editing tools and generative artificial intelligence models has made verifying the authenticity of digital images increasingly challenging, with important implications for journal…
Image Manipulation DetectionImage EditingHarmful Visual Content Manipulation Matters in Misinformation Detection Under Multimedia Scenarios
Nowadays, the widespread dissemination of misinformation across numerous social media platforms has led to severe negative effects on society. To address this challenge, the automatic detection of misinformation, particu…
Image Manipulation DetectionNeXT-IMDL: Build Benchmark for NeXT-Generation Image Manipulation Detection & Localization
The accessibility surge and abuse risks of user-friendly image editing models have created an urgent need for generalizable, up-to-date methods for Image Manipulation Detection and Localization (IMDL). Current IMDL resea…
Image Manipulation DetectionImage EditingVAAS: Vision-Attention Anomaly Scoring for Image Manipulation Detection in Digital Forensics
Recent advances in AI-driven image generation have introduced new challenges for verifying the authenticity of digital evidence in forensic investigations. Modern generative models can produce visually consistent forgeri…
Image Manipulation DetectionImage GenerationManipShield: A Unified Framework for Image Manipulation Detection, Localization and Explanation
With the rapid advancement of generative models, powerful image editing methods now enable diverse and highly realistic image manipulations that far surpass traditional deepfake techniques, posing new challenges for mani…
Image Manipulation DetectionImage EditingTraining-Free In-Context Forensic Chain for Image Manipulation Detection and Localization
Advances in image tampering pose serious security threats, underscoring the need for effective image manipulation localization (IML). While supervised IML achieves strong performance, it depends on costly pixel-level ann…
Image Manipulation LocalizationImage Manipulation DetectionDetecting Text Manipulation in Images using Vision Language Models
Recent works have shown the effectiveness of Large Vision Language Models (VLMs or LVLMs) in image manipulation detection. However, text manipulation detection is largely missing in these studies. We bridge this knowledg…
Image Manipulation DetectionWeakly-supervised Localization of Manipulated Image Regions Using Multi-resolution Learned Features
The explosive growth of digital images and the widespread availability of image editing tools have made image manipulation detection an increasingly critical challenge. Current deep learning-based manipulation detection …
Bayesian InferenceImage ManipulationImage Manipulation DetectionForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization
The field of Fake Image Detection and Localization (FIDL) is highly fragmented, encompassing four domains: deepfake detection (Deepfake), image manipulation detection and localization (IMDL), artificial intelligence-gene…
AllDeepFake DetectionFace SwappingFake Image Detection+3AnimeDL-2M: Million-Scale AI-Generated Anime Image Detection and Localization in Diffusion Era
Recent advances in image generation, particularly diffusion models, have significantly lowered the barrier for creating sophisticated forgeries, making image manipulation detection and localization (IMDL) increasingly ch…
Image GenerationImage ManipulationImage Manipulation DetectionContext-Aware Weakly Supervised Image Manipulation Localization with SAM Refinement
Malicious image manipulation poses societal risks, increasing the importance of effective image manipulation detection methods. Recent approaches in image manipulation detection have largely been driven by fully supervis…
Image ManipulationImage Manipulation DetectionImage Manipulation LocalizationLEGION: Learning to Ground and Explain for Synthetic Image Detection
The rapid advancements in generative technology have emerged as a double-edged sword. While offering powerful tools that enhance convenience, they also pose significant social concerns. As defenders, current synthetic im…
Artifact DetectionImage ManipulationImage Manipulation DetectionLarge Language Model+2IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning
Using extensive training data from SA-1B, the Segment Anything Model (SAM) has demonstrated exceptional generalization and zero-shot capabilities, attracting widespread attention in areas such as medical image segmentati…
Image ManipulationImage Manipulation DetectionImage SegmentationMedical Image Segmentation+2Data-Driven Fairness Generalization for Deepfake Detection
Despite the progress made in deepfake detection research, recent studies have shown that biases in the training data for these detectors can result in varying levels of performance across different demographic groups, su…
DeepFake DetectionFace SwappingFairnessImage Manipulation+3ForgerySleuth: Empowering Multimodal Large Language Models for Image Manipulation Detection
Multimodal large language models have unlocked new possibilities for various multimodal tasks. However, their potential in image manipulation detection remains unexplored. When directly applied to the IMD task, M-LLMs of…
Image ManipulationImage Manipulation DetectionHRGR: Enhancing Image Manipulation Detection via Hierarchical Region-aware Graph Reasoning
Image manipulation detection is to identify the authenticity of each pixel in images. One typical approach to uncover manipulation traces is to model image correlations. The previous methods commonly adopt the grids, whi…
Image ManipulationImage Manipulation DetectionPerturb, Attend, Detect and Localize (PADL): Robust Proactive Image Defense
Image manipulation detection and localization have received considerable attention from the research community given the blooming of Generative Models (GMs). Detection methods that follow a passive approach may overfit t…
AttributeImage ManipulationImage Manipulation DetectionDigital Image Forensics: A quantitative & qualitative comparison between State-of-the-art-AI and Traditional Techniques for detection and localization of image manipulations
With the rise of realistic AI-generated images and continuously advancing photo-editing software, it has become increasingly difficult to reliably distinguish between authentic and manipulated images. Using Digital Image…
Detecting Image ManipulationImage ForensicsImage Forgery DetectionImage Manipulation+4