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Kai Krajsek

2 accepted papers

2026

Self-Supervised Learning Based on Transformed Image Reconstruction for Equivariance-Coherent Feature Representation

AAAI 2026technical

Self-supervised learning (SSL) methods have achieved remarkable success in learning image representations allowing invariances in them — but therefore discarding transformation information that some computer vision tasks actually require. While recent approaches attempt to address this limitation by

Cited by 0SourcePDFScholar
2026

TimeBridge: Self-Supervised Video Representation Learning via Start-End Joint Embedding and In-Between Frame Prediction

CVPR 2026

Learning temporal transformations, that is, how visual objects evolve across frames, is a fundamental challenge in video representation learning. Frame-to-frame dynamics involve complex, non-linear, and non-local changes that go far beyond conventional spatial augmentations. We propose TimeBridge, a

Cited by 0SourceScholar