In this paper, we present a new sequence-to-sequence learning framework for visual
tracking, dubbed SeqTrack. It casts visual tracking as a sequence generation problem …

Tracking often uses a multi-stage pipeline of feature extraction, target information
integration, and bounding box estimation. To simplify this pipeline and unify the process of …

Tracking any given object (s) spatially and temporally is a common purpose in Visual Object
Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation …

Visual object tracking aims to localize the target object of each frame based on its initial
appearance in the first frame. Depending on the input modility tracking tasks can be divided …

Existing Siamese or transformer trackers commonly pose visual object tracking as a one-
shot detection problem ie locating the target object in a single forward evaluation scheme …

This study addresses the limitations of Transformer models in image feature extraction,
particularly their lack of inductive bias for visual structures. Compared to Convolutional …

Single-object tracking is a well-known and challenging research topic in computer vision.
Over the last two decades, numerous researchers have proposed various algorithms to …

The paper presents a comprehensive overview of intelligent video analytics and human
action recognition methods. The article provides an overview of the current state of …

Abstract Visual Query Localization on long-form egocentric videos requires spatio-temporal
search and localization of visually specified objects and is vital to build episodic memory …

Abstract We introduce Correlational Image Modeling (CIM), a novel but surprisingly effective
approach to self-supervised visual pre-training. Our CIM performs a simple pretext task: we …