activity
20202022
most citedHiFT: Hierarchical Feature Transformer for Aerial Tracking

11 citations · 27 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV20222 cited

TCTrack: Temporal Contexts for Aerial Tracking

Ziang Cao, Ziyuan Huang, Liang Pan +3

Temporal contexts among consecutive frames are far from being fully utilized in existing visual trackers. In this work, we present TCTrack, a comprehensive framework to fully explo…

cs.CV2022

Egocentric Prediction of Action Target in 3D

Yiming Li, Ziang Cao, Andrew Liang +4

We are interested in anticipating as early as possible the target location of a person's object manipulation action in a 3D workspace from egocentric vision. It is important in fie…

cs.CV20221 cited

Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV Tracking

Changhong Fu, Sihang Li, Xinnan Yuan +3

Visual tracking is adopted to extensive unmanned aerial vehicle (UAV)-related applications, which leads to a highly demanding requirement on the robustness of UAV trackers. However…

cs.LG20225 cited

NoisyMix: Boosting Model Robustness to Common Corruptions

N. Benjamin Erichson, Soon Hoe Lim, Winnie Xu +3

For many real-world applications, obtaining stable and robust statistical performance is more important than simply achieving state-of-the-art predictive test accuracy, and thus ro…

cs.CV202111 cited

HiFT: Hierarchical Feature Transformer for Aerial Tracking

Ziang Cao, Changhong Fu, Junjie Ye +2

Most existing Siamese-based tracking methods execute the classification and regression of the target object based on the similarity maps. However, they either employ a single map f…

cs.CV20218 cited

SiamAPN++: Siamese Attentional Aggregation Network for Real-Time UAV Tracking

Ziang Cao, Changhong Fu, Junjie Ye +2

Recently, the Siamese-based method has stood out from multitudinous tracking methods owing to its state-of-the-art (SOTA) performance. Nevertheless, due to various special challeng…