Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …

Visual target tracking is one of the most sought-after yet challenging research topics in
computer vision. Given the ill-posed nature of the problem and its popularity in a broad …

Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-
based trackers. The correlation operation is a simple fusion manner to consider the similarity …

Siamese network based trackers formulate the visual tracking task as a similarity matching
problem. Almost all popular Siamese trackers realize the similarity learning via convolutional …

By decomposing the visual tracking task into two subproblems as classification for pixel
category and regression for object bounding box at this pixel, we propose a novel fully …

Abstract We present Siam R-CNN, a Siamese re-detection architecture which unleashes the
full power of two-stage object detection approaches for visual object tracking. We combine …

Abstract The Visual Object Tracking challenge VOT2019 is the seventh annual tracker
benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; …

In this paper we illustrate how to perform both visual object tracking and semi-supervised
video object segmentation, in real-time, with a single simple approach. Our method, dubbed …

Siamese networks have drawn great attention in visual tracking because of their balanced
accuracy and speed. However, the backbone networks used in Siamese trackers are …

We introduce here a large tracking database that offers an unprecedentedly wide coverage
of common moving objects in the wild, called GOT-10k. Specifically, GOT-10k is built upon …