Papers Scale Generalisation
“Scale Generalisation” 태그가 달린 논문 3편 · 필터 해제
Scale-invariant Gaussian derivative residual networks
2026-03-03
· Andrzej Perzanowski, Tony Lindeberg
arxiv
Generalisation across image scales remains a fundamental challenge for deep networks, which often fail to handle images at scales not seen during training (the out-of-distribution problem). In this paper, we present prov…
Scale GeneralisationScale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations
2024-09-17
· Andrzej Perzanowski, Tony Lindeberg
This paper presents an in-depth analysis of the scale generalisation properties of the scale-covariant and scale-invariant Gaussian derivative networks, complemented with both conceptual and algorithmic extensions. For t…
Scale GeneralisationScale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales
2021-06-11
· Ylva Jansson, Tony Lindeberg
The ability to handle large scale variations is crucial for many real world visual tasks. A straightforward approach for handling scale in a deep network is to process an image at several scales simultaneously in a set o…
Image ClassificationScale Generalisation
1–3 / 3