Object segmentation requires both object-level information and low-level pixel data. This
presents a challenge for feedforward networks: lower layers in convolutional nets capture …

Sliding-window object detectors that generate bounding-box object predictions over a
dense, regular grid have advanced rapidly and proven popular. In contrast, modern instance …

Object proposal generation is an important and fundamental task in computer vision. In this
paper, we propose ProposalCLIP, a method towards unsupervised open-category object …

In this paper, we propose a zoom-out-and-in network for generating object proposals. A key
observation is that it is difficult to classify anchors of different sizes with the same set of …

Existing object proposal approaches use primarily bottom-up cues to rank proposals, while
we believe that" objectness" is in fact a high level construct. We argue for a data-driven …

Instance segmentation aims to detect and segment individual objects in a scene. Most
existing methods rely on precise mask annotations of every category. However, it is difficult …

The use of object proposals is an effective recent approach for increasing the computational
efficiency of object detection. We propose a novel method for generating object bounding …

Multi-scale context information has proven to be essential for object segmentation tasks.
Recent works construct the multi-scale context by aggregating convolutional feature maps …

Although deep models have greatly improved the accuracy and robustness of image
segmentation, obtaining segmentation results with highly accurate boundaries and fine …

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