[2304.02008] GlueStick: Robust Image Matching by Sticking Points and Lines Together
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. arXiv Operational Status Get status notifications via email or slack
[2304.02008] GlueStick: Robust Image Matching by Sticking Points and Lines Together Skip to main content Search arXiv Press Enter to search · Advanced search --> Computer Science > Computer Vision and Pattern Recognition arXiv:2304.02008 (cs) [Submitted on 4 Apr 2023 ( v1 ), last revised 20 Oct 2023 (this version, v3)] Title: GlueStick: Robust Image Matching by Sticking Points and Lines Together Authors: Rémi Pautrat , Iago Suárez , Yifan Yu , Marc Pollefeys , Viktor Larsson View a PDF of the paper titled GlueStick: Robust Image Matching by Sticking Points and Lines Together, by R\'emi
Explore this link on the map →related reading
- Telling Left from Right: Identifying Geometry-Aware Semantic Correspondencetelling-left-from-right.github.io
- Regularized by Score Matching (LeCun)papers.nips.cc
- Convex hull, Image processing, Image Classification, Image retrieval, Shape detectiondiva-portal.org
- A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondencesd-complements-dino.github.io
- ProtoSnap: Prototype Alignment for Cuneiform Signstau-vailab.github.io
- ReferIt3D: Neural Listeners for Fine-Grained 3D Object Identification in Real-World Scenesecva.net
- [2008.05711] Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Darxiv.org
- Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy imagesproceedings.neurips.cc
- Perspective-n-Point - Wikipediaen.wikipedia.org
- ML vs. Score matchingarxiv.org
- GitHub - xingyizhou/ExtremeNet: Bottom-up Object Detection by Grouping Extreme and Center Points · GitHubgithub.com
- GitHub - NVlabs/AutoGaze: AutoGaze automatically removes redundant patches in a video, reducing #tokens in ViT/MLLM by 4x-100x. · GitHubgithub.com