MiVOS: A Versatile Video Object Segmentation Model
MiVOS is a video object segmentation model that allows users to easily separate an object from its background in a video. This model decouples interaction-to-mask and mask propagation, making it versatile and not limited by the type of interactions.
Three Modules of MiVOS
MiVOS uses three modules: Interaction-to-Mask, Propagation, and Difference-Aware Fusion. Each module plays a crucial role in ensuring that MiVOS works efficiently to extract the object from the video.
Interaction-to-Mask Module
The interaction module is trained separately from the other two modules. It converts user interactions to an object mask, which is then temporally propagated by the propagation module using a novel top-filtering strategy in reading the space-time memory. This means that the interaction-to-mask module can be used with different types of interactions without limiting its versatility.
Propagation Module
The propagation module uses a unique top-filtering strategy in reading the space-time memory to temporally propagate the object mask. This produces accurate mask results and ensures that the model doesn't miss any component of the video frame. This module is specifically designed to work with the interaction-to-mask module, making the two modules a powerful combination.
Difference-Aware Fusion Module
To effectively take the user's intent into account, a novel difference-aware module is proposed to learn how to properly fuse the masks before and after each interaction. These masks are aligned with the target frames by employing the space-time memory. This process ensures that the model produces stable and accurate results, even when tracking fast and complex object movements.
MiVOS's three distinct modules work together to produce accurate object segmentation results in a wide range of video types. The interaction-to-mask module, propagation module, and difference-aware fusion module are capable of handling complex interactions while still producing accurate results. MiVOS is a versatile solution, not limited to any one type of interaction. With this model, users can easily extract objects from their background, making it an excellent tool for video editing or analysis.
