2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2023
DualMatch: Robust Semi-Supervised Learning with Dual-Level Interaction
Cong Wang, Xiaofeng Cao, Lanzhe Guo2 +1
Semi-supervised learning provides an expressive framework for exploiting unlabeled data when labels are insufficient. Previous semi-supervised learning methods typically match mode…
cs.CV2023★ 2 cited
Training-free Object Counting with Prompts
Zenglin Shi, Ying Sun, Mengmi Zhang
This paper tackles the problem of object counting in images. Existing approaches rely on extensive training data with point annotations for each object, making data collection labo…
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…