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Found 6 papers, 6 papers with code
VISAGE: Video Instance Segmentation with Appearance-Guided Enhancement
By effectively resolving the over-reliance on location information, we achieve state-of-the-art results on YouTube-VIS 2019/2021 and Occluded VIS (OVIS).
A Generalized Framework for Video Instance Segmentation
Notably, we greatly outperform the state-of-the-art on the long VIS benchmark (OVIS), improving 5. 6 AP with ResNet-50 backbone.
Ranked #6 on
Video Instance Segmentation
on YouTube-VIS 2021
(using extra training data)
VITA: Video Instance Segmentation via Object Token Association
Specifically, we use an image object detector as a means of distilling object-specific contexts into object tokens.
Ranked #11 on
Video Instance Segmentation
on YouTube-VIS 2021
(using extra training data)
Cannot See the Forest for the Trees: Aggregating Multiple Viewpoints to Better Classify Objects in Videos
The set classifier is plug-and-playable to existing object trackers, and highly improves the performance of long-tailed object tracking.
Video Instance Segmentation using Inter-Frame Communication Transformers
We propose a novel end-to-end solution for video instance segmentation (VIS) based on transformers.
Ranked #32 on
Video Instance Segmentation
on YouTube-VIS validation
Polygonal Point Set Tracking
Since the existing datasets are not suitable to validate our method, we build a new polygonal point set tracking dataset and demonstrate the superior performance of our method over the baselines and existing contour-based VOS methods.
