In active visual tracking, it is notoriously difficult when distracting objects appear, as distractors often mislead the tracker by occluding the target or bringing a confusing appearance. To address this issue, we propose a mixed cooperative-competitive multi-agent game, where a target and multiple distractors form a collaborative team to play against a tracker and make it fail to follow. Through learning in our game, diverse distracting behaviors of the distractors naturally emerge, thereby exposing the tracker's weakness, which helps enhance the distraction-robustness of the tracker. For effective learning, we then present a bunch of practical methods, including a reward function for distractors, a cross-modal teacher-student learning strategy, and a recurrent attention mechanism for the tracker. The experimental results show that our tracker performs desired distraction-robust active visual tracking and can be well generalized to unseen environments. We also show that the multi-agent game can be used to adversarially test the robustness of trackers.

通过提出一种混合协作-竞争多智能体游戏中的奖励函数、跨模态教师-学生学习策略和迭代注意力机制等一系列实用方法, 增强了跟踪器的抗干扰性和对干扰的鲁棒性, 从而实现了有效的干扰抗性主动视觉跟踪。实验结果表明, 该跟踪器在多种干扰干扰下表现出了优越的跟踪性能。

面向分心鲁棒的主动视觉跟踪