activity
20162023
most citedHierarchical Variational Memory for Few-shot Learning Across Domains

3 citations · 8 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023

Focus for Free in Density-Based Counting

Zenglin Shi, Pascal Mettes, Cees G. M. Snoek

This work considers supervised learning to count from images and their corresponding point annotations. Where density-based counting methods typically use the point annotations onl…

cs.LG20231 cited

MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks

Wenfang Sun, Yingjun Du, Xiantong Zhen +3

Meta-learning algorithms are able to learn a new task using previously learned knowledge, but they often require a large number of meta-training tasks which may not be readily avai…

cs.CV2023

Self-Ordering Point Clouds

Pengwan Yang, Cees G. M. Snoek, Yuki M. Asano

In this paper we address the task of finding representative subsets of points in a 3D point cloud by means of a point-wise ordering. Only a few works have tried to address this cha…

cs.LG20211 cited

Generative Kernel Continual learning

Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao +1

Kernel continual learning by \citet{derakhshani2021kernel} has recently emerged as a strong continual learner due to its non-parametric ability to tackle task interference and cata…

cs.LG20213 cited

Hierarchical Variational Memory for Few-shot Learning Across Domains

Yingjun Du, Xiantong Zhen, Ling Shao +1

Neural memory enables fast adaptation to new tasks with just a few training samples. Existing memory models store features only from the single last layer, which does not generaliz…

cs.CV20212 cited

Repetitive Activity Counting by Sight and Sound

Yunhua Zhang, Ling Shao, Cees G. M. Snoek

This paper strives for repetitive activity counting in videos. Different from existing works, which all analyze the visual video content only, we incorporate for the first time the…