3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 2 cited
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder
Jonas Dippel, Matthias Lenga, Thomas Goerttler +2
It is common practice to reuse models initially trained on different data to increase downstream task performance. Especially in the computer vision domain, ImageNet-pretrained wei…
cs.CV2021★ 3 cited
Towards Fine-grained Visual Representations by Combining Contrastive Learning with Image Reconstruction and Attention-weighted Pooling
Jonas Dippel, Steffen Vogler, Johannes Höhne
This paper presents Contrastive Reconstruction, ConRec - a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reco…