We propose an embarrassingly simple point annotation scheme to collect weak supervision
for instance segmentation. In addition to bounding boxes, we collect binary labels for a set of …

Open-vocabulary instance segmentation aims at segmenting novel classes without mask
annotations. It is an important step toward reducing laborious human supervision. Most …

Labeling data is often expensive and time-consuming, especially for tasks such as object
detection and instance segmentation, which require dense labeling of the image. While few …

We tackle the problem of localizing temporal intervals of actions with only a single frame
label for each action instance for training. Owing to label sparsity, existing work fails to learn …

In this paper, we introduce a novel learning scheme named weakly semi-supervised
instance segmentation (WSSIS) with point labels for budget-efficient and high-performance …

Nuclei detection is one of the most fundamental and challenging problems in
histopathological image analysis, which can localize nuclei to provide effective computer …

Weakly-supervised instance segmentation (WSIS) has been considered as a more
challenging task than weakly-supervised semantic segmentation (WSSS). Compared to …

The use of deep learning for water extraction requires precise pixel-level labels. However, it
is very difficult to label high-resolution remote-sensing images at the pixel level. Therefore …

Pointly supervised instance segmentation (PSIS) learns to segment objects using a single
point within the object extent as supervision. Challenged by the non-negligible semantic …

Video instance segmentation (VIS) is a challenging vision task that aims to detect segment
and track objects in videos. Conventional VIS methods rely on densely annotated object …