论文标题
Jit-Masker：有效的在线蒸馏背景垫
JIT-Masker: Efficient Online Distillation for Background Matting
论文作者
论文摘要
我们为日常使用设计了一个实时肖像贴平管道，尤其是在视频会议中的“虚拟背景”。现有的分割和贴平方法优先考虑准确性和质量而不是吞吐量和效率，我们的管道可以通过在输入视频流上利用在线蒸馏来交换可控量的准确性，以更好地吞吐量。我们在各种情况下构建了自己的模拟视频呼叫数据集，并表明我们的方法在非GPU加速设置中提供了基于显着性检测的管道的5倍加速，同时提供了更高质量的结果。我们证明，在线蒸馏方法可以作为“虚拟背景”工具的一般消费级产品的一部分可行地工作。我们的公开实施是在https://github.com/josephch405/jit-masker上。
We design a real-time portrait matting pipeline for everyday use, particularly for "virtual backgrounds" in video conferences. Existing segmentation and matting methods prioritize accuracy and quality over throughput and efficiency, and our pipeline enables trading off a controllable amount of accuracy for better throughput by leveraging online distillation on the input video stream. We construct our own dataset of simulated video calls in various scenarios, and show that our approach delivers a 5x speedup over a saliency detection based pipeline in a non-GPU accelerated setting while delivering higher quality results. We demonstrate that an online distillation approach can feasibly work as part of a general, consumer level product as a "virtual background" tool. Our public implementation is at https://github.com/josephch405/jit-masker.
