The rapid development of deep learning has made a great progress in image segmentation,
one of the fundamental tasks of computer vision. However, the current segmentation …

Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …

Observing the close relationship among panoptic, semantic and instance segmentation
tasks, we propose to train a universal multi-dataset multi-task segmentation model …

Weakly-supervised image segmentation has recently attracted increasing research
attentions, aiming to avoid the expensive pixel-wise labeling. In this paper, we present an …

In this paper, we propose a new approach to applying point-level annotations for weakly-
supervised panoptic segmentation. Instead of the dense pixel-level labels used by fully …

In this paper, we present a conceptually simple, strong, and efficient framework for fully-and
weakly-supervised panoptic segmentation, called Panoptic FCN. Our approach aims to …

Image segmentation for video analysis plays an essential role in different research fields
such as smart city, healthcare, computer vision and geoscience, and remote sensing …

Weakly supervised instance segmentation (WSIS) with only image-level labels has recently
drawn much attention. To date, bottom-up WSIS methods refine discriminative cues from …

In this paper, we introduce a novel panoptic segmentation method called the Mask-Pyramid
Network. Existing Mask RCNN-based methods first generate a large number of box …

To bridge the gap between point labels and per-pixel labels, existing point-supervised
panoptic segmentation methods usually estimate dense pseudo labels by assigning …