FlexGlue: learning when images should not match Philipp Lindenberger (@PhilippCSE) introduced FlexGlue, a model that finds image correspondences while also rejecting similar-looking images of different structures. Gabriele Berton (@gabriberton) highlighted its use of negative training examples. The paper describes joint training for matching and rejection, with early stopping on non-matching pairs. For 3D reconstruction, this addresses a practical problem: confident false matches can connect places that do not belong together. Our takeaway is that evaluation should test when a model refuses a match, alongside how accurately it finds one. Paper: https://arxiv.org/pdf/2610.32976 Code: https://github.com/cvg/FlexGlue