Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Peize Sun"'
Referring video object segmentation (R-VOS) is an emerging cross-modal task that aims to segment the target object referred by a language expression in all video frames. In this work, we propose a simple and unified framework built upon Transformer,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::472842c1b24c77866bb2583ce66173ee
http://arxiv.org/abs/2201.00487
http://arxiv.org/abs/2201.00487
Autor:
Yifu Zhang, Peize Sun, Yi Jiang, Dongdong Yu, Fucheng Weng, Zehuan Yuan, Ping Luo, Wenyu Liu, Xinggang Wang
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200465
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb5d2e9172eec975686073c03863eb7f
https://doi.org/10.1007/978-3-031-20047-2_1
https://doi.org/10.1007/978-3-031-20047-2_1
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198021
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b1f0d8cb1ed7b0ea6c5fa91deabdb08
https://doi.org/10.1007/978-3-031-19803-8_43
https://doi.org/10.1007/978-3-031-19803-8_43
A typical pipeline for multi-object tracking (MOT) is to use a detector for object localization, and following re-identification (re-ID) for object association. This pipeline is partially motivated by recent progress in both object detection and re-I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4acc7f3da59180587c1e1532ccc6d8c
http://arxiv.org/abs/2111.14690
http://arxiv.org/abs/2111.14690
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Publikováno v:
IJCAI
This work presents a new fine-grained transparent object segmentation dataset, termed Trans10K-v2, extending Trans10K-v1, the first large-scale transparent object segmentation dataset. Unlike Trans10K-v1 that only has two limited categories, our new
Publikováno v:
CVPR
In this paper, we introduce an anchor-box free and single shot instance segmentation method, which is conceptually simple, fully convolutional and can be used by easily embedding it into most off-the-shelf detection methods. Our method, termed PolarM
Autor:
Rufeng Zhang, Chenfeng Xu, Peize Sun, Wei Zhan, Tao Kong, Lei Li, Ping Luo, Masayoshi Tomizuka, Changhu Wang, Yi Jiang, Zehuan Yuan
Publikováno v:
CVPR
We present Sparse R-CNN, a purely sparse method for object detection in images. Existing works on object detection heavily rely on dense object candidates, such as $k$ anchor boxes pre-defined on all grids of image feature map of size $H\times W$. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f7efc7672f853ff02ba73c542dc6f57