Zobrazeno 1 - 10
of 3 279
pro vyhledávání: '"panoptic segmentation"'
Autor:
Liu, Zhuoran1 (AUTHOR) 202206020110@stu.bucea.edu.cn, Li, Zizhen2 (AUTHOR) lizizhen@spacestar.com.cn, Liang, Ying2 (AUTHOR) hegj@spacestar.com.cn, Persello, Claudio3 (AUTHOR) c.persello@utwente.nl, Sun, Bo4 (AUTHOR), He, Guangjun2 (AUTHOR), Ma, Lei5 (AUTHOR) maleinju@nju.edu.cn
Publikováno v:
Remote Sensing. Nov2024, Vol. 16 Issue 21, p4002. 15p.
Open-vocabulary panoptic segmentation aims to segment and classify everything in diverse scenes across an unbounded vocabulary. Existing methods typically employ two-stage or single-stage framework. The two-stage framework involves cropping the image
Externí odkaz:
http://arxiv.org/abs/2412.08628
Autor:
Stolle, Kurt H. W.
In this work, we present Multiformer, a novel approach to depth-aware video panoptic segmentation (DVPS) based on the mask transformer paradigm. Our method learns object representations that are shared across segmentation, monocular depth estimation,
Externí odkaz:
http://arxiv.org/abs/2412.07966
To help address the occlusion problem in panoptic segmentation and image understanding, this paper proposes a new large-scale dataset, COCO-Occ, which is derived from the COCO dataset by manually labelling the COCO images into three perceived occlusi
Externí odkaz:
http://arxiv.org/abs/2409.12760
Autor:
Yang, Yu, Mei, Jianbiao, Liu, Liang, Du, Siliang, Xiao, Yilin, Ra, Jongwon, Liu, Yong, Xu, Xiao, Wu, Huifeng
LiDAR panoptic segmentation, which jointly performs instance and semantic segmentation for things and stuff classes, plays a fundamental role in LiDAR perception tasks. While most existing methods explicitly separate these two segmentation tasks and
Externí odkaz:
http://arxiv.org/abs/2408.15813
This study explores the emerging area of continual panoptic segmentation, highlighting three key balances. First, we introduce past-class backtrace distillation to balance the stability of existing knowledge with the adaptability to new information.
Externí odkaz:
http://arxiv.org/abs/2407.16354
Autor:
Chakravarthy, Anirudh S, Ganesina, Meghana Reddy, Hu, Peiyun, Leal-Taixe, Laura, Kong, Shu, Ramanan, Deva, Osep, Aljosa
Addressing Lidar Panoptic Segmentation (LPS ) is crucial for safe deployment of autonomous vehicles. LPS aims to recognize and segment lidar points w.r.t. a pre-defined vocabulary of semantic classes, including thing classes of countable objects (e.g
Externí odkaz:
http://arxiv.org/abs/2409.14273
Generalist vision models aim for one and the same architecture for a variety of vision tasks. While such shared architecture may seem attractive, generalist models tend to be outperformed by their bespoken counterparts, especially in the case of pano
Externí odkaz:
http://arxiv.org/abs/2408.16504
Mammography is crucial for breast cancer surveillance and early diagnosis. However, analyzing mammography images is a demanding task for radiologists, who often review hundreds of mammograms daily, leading to overdiagnosis and overtreatment. Computer
Externí odkaz:
http://arxiv.org/abs/2407.14326
Publikováno v:
18th International Conference on Machine Vision Applications, 2023
We explore the use of deep learning to localise galactic structures in low surface brightness (LSB) images. LSB imaging reveals many interesting structures, though these are frequently confused with galactic dust contamination, due to a strong local
Externí odkaz:
http://arxiv.org/abs/2407.07494