# Learning Residual Elastic Warps for Image Stitching under Dirichlet Boundary Condition

arXiv: https://arxiv.org/abs/2309.01406 · HTML: https://mlsanity.com/paper/2309.01406/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 30 references that are in the map.
- First posted on arXiv 4 Sep 2023.

## Builds on (most cited first, 12 of 12)

- [RAFT: Recurrent All-Pairs Field Transforms for Optical Flow](https://mlsanity.com/paper/2003.12039/) (2020)
- [Deep Image Homography Estimation](https://mlsanity.com/paper/1606.03798/) (2016)
- [Accurate Optical Flow via Direct Cost Volume Processing](https://mlsanity.com/paper/1704.07325/) (2017)
- [Unsupervised Deep Image Stitching: Reconstructing Stitched Features to Images](https://mlsanity.com/paper/2106.12859/) (2021)
- [Iterative Deep Homography Estimation](https://mlsanity.com/paper/2203.15982/) (2022)
- [Parallax-Tolerant Unsupervised Deep Image Stitching](https://mlsanity.com/paper/2302.08207/) (2023)
- [Single-Perspective Warps in Natural Image Stitching](https://mlsanity.com/paper/1802.04645/) (2018)
- [Weakly-Supervised Stitching Network for Real-World Panoramic Image Generation](https://mlsanity.com/paper/2209.05968/) (2022)
- [Video Stitching for Linear Camera Arrays](https://mlsanity.com/paper/1907.13622/) (2019)
- [Learning Edge-Preserved Image Stitching from Large-Baseline Deep Homography](https://mlsanity.com/paper/2012.06194/) (2020)
- [Pixel-wise Deep Image Stitching](https://mlsanity.com/paper/2112.06171/) (2021)
- [Natural Image Stitching Using Depth Maps](https://mlsanity.com/paper/2202.06276/) (2022)

## Built on by (most cited first, 4 of 4)

- [Eliminating Warping Shakes for Unsupervised Online Video Stitching](https://mlsanity.com/paper/2403.06378/) (2024)
- [StabStitch++: Unsupervised Online Video Stitching with Spatiotemporal Bidirectional Warps](https://mlsanity.com/paper/2505.05001/) (2025)
- [LiftProj: Space Lifting and Projection-Based Panorama Stitching](https://mlsanity.com/paper/2512.24276/) (2025)
- [UniStitch: Unifying Semantic and Geometric Features for Image Stitching](https://mlsanity.com/paper/2603.10568/) (2026)

## Abstract (arXiv)

Trendy suggestions for learning-based elastic warps enable the deep image stitchings to align images exposed to large parallax errors. Despite the remarkable alignments, the methods struggle with occasional holes or discontinuity between overlapping and non-overlapping regions of a target image as the applied training strategy mostly focuses on overlap region alignment. As a result, they require additional modules such as seam finder and image inpainting for hiding discontinuity and filling holes, respectively. In this work, we suggest Recurrent Elastic Warps (REwarp) that address the problem with Dirichlet boundary condition and boost performances by residual learning for recurrent misalign correction. Specifically, REwarp predicts a homography and a Thin-plate Spline (TPS) under the boundary constraint for discontinuity and hole-free image stitching. Our experiments show the favorable aligns and the competitive computational costs of REwarp compared to the existing stitching methods. Our source code is available at https://github.com/minshu-kim/REwarp.