Transformer

TCTrack: Temporal Contexts for Aerial Tracking

Temporal contexts among consecutive frames are far from been fully utilized in existing visual trackers. In this work, we present TCTrack1, a comprehensive framework to fully exploit temporal contexts for aerial tracking. The temporal contexts are …

Unsupervised Domain Adaptation for Nighttime Aerial Tracking

Previous advances in object tracking mostly reported on favorable illumination circumstances while neglecting performance at nighttime, which significantly impeded the development of related aerial robot applications. This work instead develops a …

Tracker Meets Night: A Transformer Enhancer for UAV Tracking

Most previous progress in object tracking is realized in daytime scenes with favorable illumination. State-of-the-arts can hardly carry on their superiority at night so far, thereby considerably blocking the broadening of visual tracking-related …

HiFT: Hierarchical Feature Transformer for Aerial Tracking

Siamese-based visual tracking methods generally execute the classification and regression of the target object based on the similarity maps. However, existing works either solely employ a single map generated by the last convolutional layer which …