VisTR
VisTR
**VisTR** is a [Transformer](https://paperswithcode.com/method/transformer) based video instance segmentation model. It views video instance segmentation as a direct end-to-end parallel sequence decoding/prediction problem. Given a video clip consisting of multiple image frames as input, VisTR outputs the sequence of masks for each instance in the video in order directly. At the core is a new, effective instance sequence matching and segmentation strategy, which supervises and segments instances at the sequence level as a whole. VisTR frames the instance segmentation and tracking in the same perspective of similarity learning, thus considerably simplifying the overall pipeline and is significantly different from existing approaches.
End-to-End Video Instance Segmentation with Transformers
https://paperswithcode.com/paper/end-to-end-video-instance-segmentation-with
End-to-End Video Instance Segmentation with Transformers