Multi-object tracking (MOT) is an essential task in the computer vision field. With the fast development of deep learning technology in recent years, MOT has achieved great improvement. However, some challenges still remain, such as sensitiveness to occlusion, instability under different lighting conditions, non-robustness to deformable objects, etc. To address such common challenges in most of the existing trackers, in this paper, a tracklet booster algorithm is proposed, which can be built upon any other tracker. The motivation is simple and straightforward: split tracklets on potential ID-switch positions and then connect multiple tracklets into one if they are from the same object. In other words, the tracklet booster consists of two parts, i.e., Splitter and Connector. First, an architecture with stacked temporal dilated convolution blocks is employed for the splitting position prediction via label smoothing strategy with adaptive Gaussian kernels. Then, a multi-head self-attention based encoder is exploited for the tracklet embedding, which is further used to connect tracklets into larger groups. We conduct sufficient experiments on MOT17 and MOT20 benchmark datasets, which demonstrates promising results. Combined with the proposed tracklet booster, existing trackers usually can achieve large improvements on the IDF1 score, which shows the effectiveness of the proposed method.

中文翻译：

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拆分并连接：用于多对象跟踪的通用Tracklet Booster

在计算机视觉领域，多目标跟踪（MOT）是一项必不可少的任务。近年来，随着深度学习技术的飞速发展，MOT取得了长足的进步。但是，仍然存在一些挑战，例如对遮挡的敏感性，在不同光照条件下的不稳定性，对可变形物体的不稳健性等。为了解决大多数现有跟踪器中的此类常见挑战，本文提出了一种Tracklet Booster算法，它可以建立在任何其他跟踪器上。动机很简单明了：在潜在的ID开关位置上拆分小跟踪，然后将多个小跟踪（如果它们来自同一对象）连接成一个小跟踪。换句话说，小径助推器由两部分组成，即分离器和连接器。第一的，通过使用带有自适应高斯核的标签平滑策略，将具有堆叠的时间膨胀卷积块的体系结构用于分割位置预测。然后，利用基于多头自注意的编码器进行小波嵌入，该编码器进一步用于将小波连接成更大的组。我们对MOT17和MOT20基准数据集进行了足够的实验，证明了令人鼓舞的结果。结合拟议的小波助推器，现有的跟踪器通常可以在IDF1分数上实现较大的改进，这表明了所提方法的有效性。进一步用于将小轨迹连接成更大的组。我们对MOT17和MOT20基准数据集进行了足够的实验，证明了令人鼓舞的结果。结合拟议的小波助推器，现有的跟踪器通常可以在IDF1分数上实现较大的改进，这表明了所提方法的有效性。进一步用于将小轨迹连接成更大的组。我们对MOT17和MOT20基准数据集进行了足够的实验，证明了令人鼓舞的结果。结合拟议的小波助推器，现有的跟踪器通常可以在IDF1分数上实现较大的改进，这表明了所提方法的有效性。