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 …

Visible-modal object tracking gives rise to a series of downstream multi-modal tracking
tributaries. To inherit the powerful representations of the foundation model, a natural modus …

This report presents a framework called Segment And Track Anything (SAMTrack) that
allows users to precisely and effectively segment and track any object in a video …

Recently, the Segment Anything Model (SAM) gains lots of attention rapidly due to its
impressive segmentation performance on images. Regarding its strong ability on image …

Transformer-based trackers have achieved strong accuracy on the standard benchmarks.
However, their efficiency remains an obstacle to practical deployment on both GPU and …

In the realm of video object tracking auxiliary modalities such as depth thermal or event data
have emerged as valuable assets to complement the RGB trackers. In practice most existing …

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 …