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 …

Image segmentation refers to the process to divide an image into meaningful non-
overlap** regions according to human perception, which has become a classic topic since …

Grou** and recognition are important components of visual scene understanding, eg, for
object detection and semantic segmentation. With end-to-end deep learning systems …

In this paper, we study the context aggregation problem in semantic segmentation.
Motivated by that the label of a pixel is the category of the object that the pixel belongs to, we …

Object detection, one of the most fundamental and challenging problems in computer vision,
seeks to locate object instances from a large number of predefined categories in natural …

Object detection performance, as measured on the canonical PASCAL VOC Challenge
datasets, plateaued in the final years of the competition. The best-performing methods were …

Pixel-level labelling tasks, such as semantic segmentation, play a central role in image
understanding. Recent approaches have attempted to harness the capabilities of deep …

Object proposals have become an integral pre-processing step of many vision pipelines
including object detection, weakly supervised detection, object discovery, tracking, etc …

Object detection performance, as measured on the canonical PASCAL VOC dataset, has
plateaued in the last few years. The best-performing methods are complex ensemble …

We aim to detect all instances of a category in an image and, for each instance, mark the
pixels that belong to it. We call this task Simultaneous Detection and Segmentation (SDS) …