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pro vyhledávání: '"Hwang, Sukjun"'
A wide array of sequence models are built on a framework modeled after Transformers, comprising alternating sequence mixer and channel mixer layers. This paper studies a unifying matrix mixer view of sequence mixers that can be conceptualized as a li
Externí odkaz:
http://arxiv.org/abs/2407.09941
In recent years, online Video Instance Segmentation (VIS) methods have shown remarkable advancement with their powerful query-based detectors. Utilizing the output queries of the detector at the frame-level, these methods achieve high accuracy on cha
Externí odkaz:
http://arxiv.org/abs/2312.04885
Autor:
Heo, Miran, Hwang, Sukjun, Hyun, Jeongseok, Kim, Hanjung, Oh, Seoung Wug, Lee, Joon-Young, Kim, Seon Joo
The handling of long videos with complex and occluded sequences has recently emerged as a new challenge in the video instance segmentation (VIS) community. However, existing methods have limitations in addressing this challenge. We argue that the big
Externí odkaz:
http://arxiv.org/abs/2211.08834
We introduce a novel paradigm for offline Video Instance Segmentation (VIS), based on the hypothesis that explicit object-oriented information can be a strong clue for understanding the context of the entire sequence. To this end, we propose VITA, a
Externí odkaz:
http://arxiv.org/abs/2206.04403
Recently, both long-tailed recognition and object tracking have made great advances individually. TAO benchmark presented a mixture of the two, long-tailed object tracking, in order to further reflect the aspect of the real-world. To date, existing s
Externí odkaz:
http://arxiv.org/abs/2206.02116
Autor:
Han, Su Ho, Hwang, Sukjun, Oh, Seoung Wug, Park, Yeonchool, Kim, Hyunwoo, Kim, Min-Jung, Kim, Seon Joo
For online video instance segmentation (VIS), fully utilizing the information from previous frames in an efficient manner is essential for real-time applications. Most previous methods follow a two-stage approach requiring additional computations suc
Externí odkaz:
http://arxiv.org/abs/2112.04177
We propose a novel end-to-end solution for video instance segmentation (VIS) based on transformers. Recently, the per-clip pipeline shows superior performance over per-frame methods leveraging richer information from multiple frames. However, previou
Externí odkaz:
http://arxiv.org/abs/2106.03299
Panoptic segmentation, which is a novel task of unifying instance segmentation and semantic segmentation, has attracted a lot of attention lately. However, most of the previous methods are composed of multiple pathways with each pathway specialized t
Externí odkaz:
http://arxiv.org/abs/2012.01632
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Panoptic segmentation, which is a novel task of unifying instance segmentation and semantic segmentation, has attracted a lot of attention lately. However, most of the previous methods are composed of multiple pathways with each pathway specialized t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c7e81bda22aff6a3ba07ea943bbeae5
https://doi.org/10.1109/wacv51458.2022.00200
https://doi.org/10.1109/wacv51458.2022.00200
