Search Results for author:
Found 7 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.
VISOLO: Grid-Based Space-Time Aggregation for Efficient Online Video Instance Segmentation
We also introduce cooperatively operating modules that aggregate information from available frames, in order to enrich the features for all subtasks in VIS.
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
Single-shot Path Integrated Panoptic Segmentation
Panoptic segmentation, which is a novel task of unifying instance segmentation and semantic segmentation, has attracted a lot of attention lately.
