mlsanityData to 7 Oct 2026

SeeTheSeams: Localized Detection of Seam Carving based Image Forgery in Satellite Imagery

arXiv 2108.12534 ↗First posted 28 Aug 2021cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Seam carving is a popular technique for content aware image retargeting. It can be used to deliberately manipulate images, for example, change the GPS locations of a building or insert/remove roads in a satellite image. This paper proposes a novel approach for detecting and localizing seams in such images. While there are methods to detect seam carving based manipulations, this is the first time that robust localization and detection of seam carving forgery is made possible. We also propose a seam localization score (SLS) metric to evaluate the effectiveness of localization. The proposed method is evaluated extensively on a large collection of images from different sources, demonstrating a high level of detection and localization performance across these datasets. The datasets curated during this work will be released to the public.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 68 references that are in the map. First posted on arXiv 28 Aug 2021.

Builds on

16 of 68 references.

References · 16

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  4. 2018xView: Objects in Context in Overhead Imagerycited by 145
  5. 2019xBD: A Dataset for Assessing Building Damage from Satellite Imagerycited by 138
  6. 2017Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)cited by 64
  7. 2019Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeriescited by 59
  8. 2018You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagerycited by 27
  9. 2020Detection, Attribution and Localization of GAN Generated Imagescited by 24
  10. 2018Satellite Image Forgery Detection and Localization Using GAN and One-Class Classifiercited by 14
  11. 2017Detection and Localization of Image Forgeries using Resampling Features and Deep Learningcited by 13
  12. 2020Deep Convolutional Neural Network for Identifying Seam-Carving Forgerycited by 9
4 more
  1. 2020Generative Autoregressive Ensembles for Satellite Imagery Manipulation Detectioncited by 6
  2. 2018Boosting Image Forgery Detection using Resampling Features and Copy-move analysiscited by 3
  3. 2018Resampling Forgery Detection Using Deep Learning and A-Contrario Analysiscited by 2
  4. 2021Holistic Image Manipulation Detection using Pixel Co-occurrence Matricescited by 2

Built on by

Not cited yet.