论文标题
重新访问基于点击的交互式视频对象细分
Revisiting Click-based Interactive Video Object Segmentation
论文作者
论文摘要
尽管当前的交互式视频对象细分（IVO）依靠基于涂鸦的交互来生成精确的对象掩码，但我们建议基于点击的交互式视频对象细分（CIVOS）框架，以尽可能简化所需的用户工作负载。 CIVOS建立在反映用户互动和掩盖传播的DE耦合模块的基础上。交互模块将基于点击的交互转换为对象掩码，然后通过传播模块推断为其余帧。其他用户交互允许对象蒙版进行改进。该方法对流行的交互式〜戴维斯数据集进行了广泛的评估，但不可避免地适应了基于点击的基于点击的互动。我们考虑了在评估过程中生成点击的几种策略，以反映各种用户输入，并调整戴维斯性能指标以执行与硬件无关的比较。提出的CIVOS管道取得了竞争成果，尽管需要较低的用户工作量。
While current methods for interactive Video Object Segmentation (iVOS) rely on scribble-based interactions to generate precise object masks, we propose a Click-based interactive Video Object Segmentation (CiVOS) framework to simplify the required user workload as much as possible. CiVOS builds on de-coupled modules reflecting user interaction and mask propagation. The interaction module converts click-based interactions into an object mask, which is then inferred to the remaining frames by the propagation module. Additional user interactions allow for a refinement of the object mask. The approach is extensively evaluated on the popular interactive~DAVIS dataset, but with an inevitable adaptation of scribble-based interactions with click-based counterparts. We consider several strategies for generating clicks during our evaluation to reflect various user inputs and adjust the DAVIS performance metric to perform a hardware-independent comparison. The presented CiVOS pipeline achieves competitive results, although requiring a lower user workload.
