Efficient Video Object Segmentation via Network Modulation

Understand

Video object segmentation targets at segmenting a specific object throughout a video sequence, given only an annotated first frame.

• Recent deep learning based approaches find it effective by fine-tuning a general-purpose segmentation model on the annotated frame using hundreds of iterations of gradient descent.
• Despite the high accuracy these methods achieve, the fine-tuning process is inefficient and fail to meet the requirements of real world applications.
• We propose a novel approach that uses a single forward pass to adapt the segmentation model to the appearance of a specific object.