图像分割是指将图像分成若干具有相似性质的区域的过程, 是许多图像处理任务的预处理步骤.
近年来, 国内外学者主要研究基于图像内容的分割算法. 在广泛调研大量文献和最新成果的基础 …

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 …

图像分割是指将图像分成若干具有相似性质的区域的过程, 是许多图像处理任务的预处理步骤.
近年来, 国内外学者主要研究基于图像内容的分割算法. 在广泛调研大量文献和最新成果的基础 …

By taking the semantic object parsing task as an exemplar application scenario, we propose
the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of …

Deep convolutional neural networks (CNNs) are the backbone of state-of-art semantic
image segmentation systems. Recent work has shown that complementing CNNs with fully …

We address the problem of semantic segmentation using deep learning. Most segmentation
systems include a Conditional Random Field (CRF) to produce a structured output that is …

In this work we propose a structured prediction technique that combines the virtues of
Gaussian Conditional Random Fields (G-CRF) with Deep Learning:(a) our structured …

Parsing articulated objects, eg. humans and animals, into semantic parts (eg. head, body
and arms, etc.) from natural images is a challenging and fundamental problem in computer …

This paper presents a novel method to involve both spatial and temporal features for
semantic video segmentation. Current work on convolutional neural networks (CNNs) has …

To make reliable diagnosis, pathologists often need to identify certain special regions in
medical images. In inflammatory bowel disease (IBD) diagnosis via histology tissue image …