Video Object Segmentation, and video processing in general, has been historically
dominated by methods that rely on the temporal consistency and redundancy in consecutive …

The problem of video object segmentation can become extremely challenging when multiple
instances co-exist. While each instance may exhibit large scale and pose variations, the …

Convolutional networks reach top quality in pixel-level video object segmentation but
require a large amount of training data (1k–100k) to deliver such results. We propose a new …

This paper presents a method for detecting salient objects in videos, where temporal
information in addition to spatial information is fully taken into account. Following recent …

Re-identifying objects in a rigid scene across varying viewpoints (object Re-ID) is a
challenging task, in particular when there are similar, even identical objects coexist in the …

We tackle the task of semi-supervised video object segmentation, ie pixel-level object
classification of the images in video sequences using very limited ground truth training data …

Focusing on only semantic instances that only salient in a scene gains more benefits for
robot navigation and self-driving cars than looking at all objects in the whole scene. This …

In this paper, we introduce a practical system for interactive video object mask annotation,
which can support multiple back-end methods. To demonstrate the generalization of our …

In this paper, we propose a novel Guided Instance Segmentation (GIS) framework to tackle
the challenging problem of semi-supervised video instance segmentation. To improve the …

In this paper, we propose a novel Multi-Referenced Guided Instance Segmentation (MR-
GIS) framework for the challenging problem of semi-supervised video instance …