Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Xu, Yuanyou"'
Powered by large-scale text-to-image generation models, text-to-3D avatar generation has made promising progress. However, most methods fail to produce photorealistic results, limited by imprecise geometry and low-quality appearance. Towards more pra
Externí odkaz:
http://arxiv.org/abs/2312.08889
Tracking any given object(s) spatially and temporally is a common purpose in Visual Object Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation have been attempted in some studies but they often lack full compatibility
Externí odkaz:
http://arxiv.org/abs/2308.13266
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object tracking and segmentation. In this study, we convert the bounding boxes to masks in reference frames
Externí odkaz:
http://arxiv.org/abs/2307.02508
The Associating Objects with Transformers (AOT) framework has exhibited exceptional performance in a wide range of complex scenarios for video object segmentation. In this study, we introduce MSDeAOT, a variant of the AOT series that incorporates tra
Externí odkaz:
http://arxiv.org/abs/2307.02010
This report presents a framework called Segment And Track Anything (SAMTrack) that allows users to precisely and effectively segment and track any object in a video. Additionally, SAM-Track employs multimodal interaction methods that enable users to
Externí odkaz:
http://arxiv.org/abs/2305.06558
In this paper, we introduce semi-supervised video object segmentation (VOS) to panoptic wild scenes and present a large-scale benchmark as well as a baseline method for it. Previous benchmarks for VOS with sparse annotations are not sufficient to tra
Externí odkaz:
http://arxiv.org/abs/2305.04470
Autor:
Xie, Peilu1 (AUTHOR), Xu, Yuanyou1 (AUTHOR), Tang, Jiaxin1 (AUTHOR), Wu, Shihua1 (AUTHOR) drwushihua@zju.edu.cn, Gao, Haichun1 (AUTHOR) haichung@zju.edu.cn
Publikováno v:
Communications Biology. 4/26/2024, Vol. 7 Issue 1, p1-15. 15p.
Akademický článek
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Panoramic images have advantages in information capacity and scene stability due to their large field of view (FoV). In this paper, we propose a method to synthesize a new dataset of panoramic image. We managed to stitch the images taken from differe
Externí odkaz:
http://arxiv.org/abs/1909.00532
Akademický článek
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