activity
20232026
most citedAugmentation-aware Self-supervised Learning with Conditioned Projector

7 citations · 9 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

WildMatch: Weakly Supervised Image Matcher Adaptation for Wildlife Re-Identification

Turhan Can Kargin, Piotr Kubaty, Ekaterina Rostovskaya +3

Individual animal re-identification from camera-trap imagery is an instance retrieval problem central to non-invasive wildlife monitoring: a query image must retrieve the correct i…

cs.CV2024

Beyond [cls]: Exploring the true potential of Masked Image Modeling representations

Marcin Przewięźlikowski, Randall Balestriero, Wojciech Jasiński +2

Masked Image Modeling (MIM) has emerged as a promising approach for Self-Supervised Learning (SSL) of visual representations. However, the out-of-the-box performance of MIMs is typ…

cs.LG2024

A deep cut into Split Federated Self-supervised Learning

Marcin Przewięźlikowski, Marcin Osial, Bartosz Zieliński +1

Collaborative self-supervised learning has recently become feasible in highly distributed environments by dividing the network layers between client devices and a central server. H…

cs.LG2023★ 2 cited

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning

Filip Szatkowski, Mateusz Pyla, Marcin Przewięźlikowski +3

In this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KD-based me…

cs.CV2023★ 7 cited

Augmentation-aware Self-supervised Learning with Conditioned Projector

Marcin Przewięźlikowski, Mateusz Pyla, Bartosz Zieliński +3

Self-supervised learning (SSL) is a powerful technique for learning from unlabeled data. By learning to remain invariant to applied data augmentations, methods such as SimCLR and M…