mlsanityData to 14 Oct 2026

Retargeting Visual Data with Deformation Fields

arXiv 2311.13297 ↗First posted 22 Nov 2023cs.CVcited by 3

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Abstract (arXiv)

Seam carving is an image editing method that enable content-aware resizing, including operations like removing objects. However, the seam-finding strategy based on dynamic programming or graph-cut limits its applications to broader visual data formats and degrees of freedom for editing. Our observation is that describing the editing and retargeting of images more generally by a displacement field yields a generalisation of content-aware deformations. We propose to learn a deformation with a neural network that keeps the output plausible while trying to deform it only in places with low information content. This technique applies to different kinds of visual data, including images, 3D scenes given as neural radiance fields, or even polygon meshes. Experiments conducted on different visual data show that our method achieves better content-aware retargeting compared to previous methods.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 34 of its 64 references that are in the map. First posted on arXiv 22 Nov 2023.

Builds on

34 of 64 references.

References · 34

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22 more
  1. 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 759
  2. 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 737
  3. 2019SinGAN: Learning a Generative Model from a Single Natural Imagecited by 348
  4. 2018Analyzing Inverse Problems with Invertible Neural Networkscited by 242
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  8. 2021Enhancing Photorealism Enhancementcited by 74
  9. 2023Matryoshka Diffusion Modelscited by 72
  10. 2022Neural Surface Reconstruction of Dynamic Scenes with Monocular RGB-D Cameracited by 57
  11. 2019Learning a Neural 3D Texture Space from 2D Exemplarscited by 53
  12. 2020Deep Geometric Texture Synthesiscited by 51
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  14. 2022VolTeMorph: Realtime, Controllable and Generalisable Animation of Volumetric Representationscited by 36
  15. 2021Generative Modelling of BRDF Textures from Flash Imagescited by 35
  16. 2022Learning to Generate 3D Shapes from a Single Examplecited by 31
  17. 2023Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shapecited by 29
  18. 2019Cycle-IR: Deep Cyclic Image Retargetingcited by 14
  19. 2020Deep Convolutional Neural Network for Identifying Seam-Carving Forgerycited by 9
  20. 2020Self-Play Reinforcement Learning for Fast Image Retargetingcited by 7
  21. 2021Seam Carving Detection and Localization using Two-Stage Deep Neural Networkscited by 2
  22. 2022An End-to-End Approach for Seam Carving Detection using Deep Neural Networkscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025HALO: Human-Aligned End-to-end Image Retargeting with Layered Transformationscited by 1
  2. 2025Object-IR: Leveraging Object Consistency and Mesh Deformation for Self-Supervised Image Retargetingcited by 1
  3. 2026AttenIR: Aligning Dense Visual Attention with Mesh Warping for Unsupervised Image Retargetingcited by 0