G Ghiasi, CC Fowlkes - Computer Vision–ECCV 2016: 14th European …, 2016 - Springer
CNN architectures have terrific recognition performance but rely on spatial pooling which makes it difficult to adapt them to tasks that require dense, pixel-accurate labeling. This …
In recent years, we have seen tremendous progress in the field of object detection. Most of the recent improvements have been achieved by targeting deeper feedforward networks …
Deep learning has considerably improved semantic image segmentation. However, its high accuracy is traded against larger computational costs which makes it unsuit-able for …
The recent COCO object detection dataset presents several new challenges for object detection. In particular, it contains objects at a broad range of scales, less prototypical …
Inspired by recent advances of deep learning in instance segmentation and object tracking, we introduce video object segmentation problem as a concept of guided instance …
M Januszewski, J Maitin-Shepard, P Li… - arXiv preprint arXiv …, 2016 - arxiv.org
State-of-the-art image segmentation algorithms generally consist of at least two successive and distinct computations: a boundary detection process that uses local image information to …
We address the problem of instance-level semantic segmentation, which aims at jointly detecting, segmenting and classifying every individual object in an image. In this context …
L Jin, Z Chen, Z Tu - arXiv preprint arXiv:1611.08991, 2016 - arxiv.org
Instance segmentation has attracted recent attention in computer vision and existing methods in this domain mostly have an object detection stage. In this paper, we study the …
Y Xu, Y Li, M Liu, Y Wang, Y Fan, M Lai… - arXiv preprint arXiv …, 2016 - arxiv.org
In this paper, we propose a new image instance segmentation method that segments individual glands (instances) in colon histology images. This is a task called instance …