# WxBS: Wide Baseline Stereo Generalizations

arXiv: https://arxiv.org/abs/1504.06603 · HTML: https://mlsanity.com/paper/1504.06603/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Apr 2015.

## Built on by (most cited first, 23 of 23)

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- [UFM: A Simple Path towards Unified Dense Correspondence with Flow](https://mlsanity.com/paper/2506.09278/) (2025)
- [Local Feature Matching Using Deep Learning: A Survey](https://mlsanity.com/paper/2401.17592/) (2024)
- [Wide-Baseline Multi-Camera Calibration using Person Re-Identification](https://mlsanity.com/paper/2104.08568/) (2021)
- [FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation](https://mlsanity.com/paper/2403.03221/) (2024)
- [LoMa: Local Feature Matching Revisited](https://mlsanity.com/paper/2604.04931/) (2026)
- [Deep Learning Reforms Image Matching: A Survey and Outlook](https://mlsanity.com/paper/2506.04619/) (2025)
- [Affine steerers for structured keypoint description](https://mlsanity.com/paper/2408.14186/) (2024)
- [Image Matching by Bare Homography](https://mlsanity.com/paper/2305.08946/) (2023)
- [Dense Match Summarization for Faster Two-view Estimation](https://mlsanity.com/paper/2506.02893/) (2025)
- [PanMatch: Unleashing the Potential of Large Vision Models for Unified Matching Models](https://mlsanity.com/paper/2507.08400/) (2025)
- [Multimodal Image Matching based on Frequency-domain Information of Local Energy Response](https://mlsanity.com/paper/2503.20827/) (2025)
- [UFM: Unified Feature Matching Pre-training with Multi-Modal Image Assistants](https://mlsanity.com/paper/2503.21820/) (2025)
- [Who Handles Orientation? Investigating Invariance in Feature Matching](https://mlsanity.com/paper/2604.11809/) (2026)
- [CasCalib: Cascaded Calibration for Motion Capture from Sparse Unsynchronized Cameras](https://mlsanity.com/paper/2405.06845/) (2024)
- [Automatic Die Studies for Ancient Numismatics](https://mlsanity.com/paper/2407.20876/) (2024)
- [RoMa-Omega: What Feed-Forward 3D Models Know About Image Matching](https://mlsanity.com/paper/2609.09507/) (2026)
- [FAST: Flow Any Scene Transformer](https://mlsanity.com/paper/2609.39748/) (2026)

## Abstract (arXiv)

We have presented a new problem -- the wide multiple baseline stereo (WxBS) -- which considers matching of images that simultaneously differ in more than one image acquisition factor such as viewpoint, illumination, sensor type or where object appearance changes significantly, e.g. over time. A new dataset with the ground truth for evaluation of matching algorithms has been introduced and will be made public. We have extensively tested a large set of popular and recent detectors and descriptors and show than the combination of RootSIFT and HalfRootSIFT as descriptors with MSER and Hessian-Affine detectors works best for many different nuisance factors. We show that simple adaptive thresholding improves Hessian-Affine, DoG, MSER (and possibly other) detectors and allows to use them on infrared and low contrast images. A novel matching algorithm for addressing the WxBS problem has been introduced. We have shown experimentally that the WxBS-M matcher dominantes the state-of-the-art methods both on both the new and existing datasets.