The objective of this paper is a model that is able to discover, track and segment multiple
moving objects in a video. We make four contributions: First, we introduce an object-centric …

Humans can easily detect and segment moving objects simply by observing how they move,
even without knowledge of object semantics. Inspired by this, we develop a zero-shot …

We present the 2019 DAVIS Challenge on Video Object Segmentation, the third edition of
the DAVIS Challenge series, a public competition designed for the task of Video Object …

As a bio-inspired sensor with high temporal resolution, the spiking camera has an enormous
potential in real applications, especially for motion estimation in high-speed scenes …

Recent work in unsupervised multi-object segmentation shows impressive results by
predicting motion from a single image despite the inherent ambiguity in predicting motion …

Appearance-based detectors achieve remarkable performance on common scenes,
benefiting from high-capacity models and massive annotated data, but tend to fail for …

The goal of motion segmentation is to segregate a visual scene into independently moving
objects. It is an indispensable pre-processing step for various tasks in computer vision and …

Abstract We address Unsupervised Video Object Segmentation (UVOS), the task of
automatically generating accurate pixel masks for salient objects in a video sequence and of …

Motion, measured via optical flow, provides a powerful cue to discover and learn objects in
images and videos. However, compared to using appearance, it has some blind spots, such …

Detecting and segmenting individual objects, regardless of their category, is crucial for many
applications such as action detection or robotic interaction. While this problem has been well …