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Found 2 papers, 1 papers with code
SIM2E: Benchmarking the Group Equivariant Capability of Correspondence Matching Algorithms
The experimental results demonstrate the importance of group equivariant algorithms for correspondence matching on various sim(2) transformation conditions.
XCon: Learning with Experts for Fine-grained Category Discovery
We address the problem of generalized category discovery (GCD) in this paper, i. e. clustering the unlabeled images leveraging the information from a set of seen classes, where the unlabeled images could contain both seen classes and unseen classes.
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