Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …

We survey research on self-driving cars published in the literature focusing on autonomous
cars developed since the DARPA challenges, which are equipped with an autonomy system …

We present ARTrack, an autoregressive framework for visual object tracking. ARTrack
tackles tracking as a coordinate sequence interpretation task that estimates object …

In this paper, we present a new tracking architecture with an encoder-decoder transformer
as the key component. The encoder models the global spatio-temporal feature …

In video object tracking, there exist rich temporal contexts among successive frames, which
have been largely overlooked in existing trackers. In this work, we bridge the individual …

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 …

Tracking has traditionally been the art of following interest points through space and time.
This changed with the rise of powerful deep networks. Nowadays, tracking is dominated by …

Siamese tracking has achieved groundbreaking performance in recent years, where the
essence is the efficient matching operator cross-correlation and its variants. Besides the …

Visual tracking is fundamentally the problem of regressing the state of the target in each
video frame. While significant progress has been achieved, trackers are still prone to failures …

The current strive towards end-to-end trainable computer vision systems imposes major
challenges for the task of visual tracking. In contrast to most other vision problems, tracking …