3 citations · 3 across the 6 of their papers we have counts for
7 papers
Can Image Splicing and Copy-Move Forgery Be Detected by the Same Model? Forensim: An Attention-Based State-Space Approach
Soumyaroop Nandi, Prem Natarajan
We introduce Forensim, an attention-based state-space framework for image forgery detection that jointly localizes both manipulated (target) and source regions. Unlike traditional…
BioTamperNet: Affinity-Guided State-Space Model Detecting Tampered Biomedical Images
Soumyaroop Nandi, Prem Natarajan
We propose BioTamperNet, a novel framework for detecting duplicated regions in tampered biomedical images, leveraging affinity-guided attention inspired by State Space Model (SSM)…
Rescind: Countering Image Misconduct in Biomedical Publications with Vision-Language and State-Space Modeling
Soumyaroop Nandi, Prem Natarajan
Scientific image manipulation in biomedical publications poses a growing threat to research integrity and reproducibility. Unlike natural image forensics, biomedical forgery detect…
TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization
Soumyaroop Nandi, Prem Natarajan, Wael Abd-Almageed
The evaluation datasets and metrics for image manipulation detection and localization (IMDL) research have been standardized. But the training dataset for such a task is still nons…
MONet: Multi-scale Overlap Network for Duplication Detection in Biomedical Images
Ekraam Sabir, Soumyaroop Nandi, Wael AbdAlmageed +1
Manipulation of biomedical images to misrepresent experimental results has plagued the biomedical community for a while. Recent interest in the problem led to the curation of a dat…
BioFors: A Large Biomedical Image Forensics Dataset
Ekraam Sabir, Soumyaroop Nandi, Wael AbdAlmageed +1
Research in media forensics has gained traction to combat the spread of misinformation. However, most of this research has been directed towards content generated on social media.…
SIGN: Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentation
Jiaxin Cheng, Soumyaroop Nandi, Prem Natarajan +1
Unlike conventional zero-shot classification, zero-shot semantic segmentation predicts a class label at the pixel level instead of the image level. When solving zero-shot semantic…