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VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learning [article]

Mengyang Zhao, Quan Liu, Aadarsh Jha, Ruining Deng, Tianyuan Yao, Anita Mahadevan-Jansen, Matthew J.Tyska, Bryan A. Millis, Yuankai Huo
2021 arXiv   pre-print
embedding; (3) Accomplished an end-to-end framework for one-stage 3D cell instance segmentation and tracking without heavy parameter tuning; (4) The proposed 3D quantification is memory efficient via  ...  In this work, we propose a novel spatial-temporal voxel-embedding (VoxelEmbed) based learning method to perform simultaneous cell instance segmenting and tracking on 3D volumetric video sequences.  ...  As opposed to deploying a 3D network, we develop a simple multi-stream learning approach to learn spatial, temporal, and 3D context information simultaneously via a 2D network design.  ... 
arXiv:2106.11480v1 fatcat:crnya3pi6jgttavf7fm7l33z34

Video Object Detection with an Aligned Spatial-Temporal Memory [article]

Fanyi Xiao, Yong Jae Lee
2018 arXiv   pre-print
We introduce Spatial-Temporal Memory Networks for video object detection.  ...  Furthermore, in order to tackle object motion in videos, we propose a novel MatchTrans module to align the spatial-temporal memory from frame to frame.  ...  Furthermore, each region feature can be extracted trivially via ROI pooling from the memory. In summary, our main contribution is a novel spatial-temporal memory network for video object detection.  ... 
arXiv:1712.06317v3 fatcat:3ms7g5pgwvgr3kcxa2rz3jn3ou

Video Object Detection with an Aligned Spatial-Temporal Memory [chapter]

Fanyi Xiao, Yong Jae Lee
2018 Lecture Notes in Computer Science  
We introduce Spatial-Temporal Memory Networks for video object detection.  ...  Furthermore, in order to tackle object motion in videos, we propose a novel MatchTrans module to align the spatial-temporal memory from frame to frame.  ...  Furthermore, each region feature can be extracted trivially via ROI pooling from the memory. In summary, our main contribution is a novel spatial-temporal memory network for video object detection.  ... 
doi:10.1007/978-3-030-01237-3_30 fatcat:g24c756uzrgh7aa7plko45yrni

End-to-End Video Object Detection with Spatial-Temporal Transformers [article]

Lu He, Qianyu Zhou, Xiangtai Li, Li Niu, Guangliang Cheng, Xiao Li, Wenxuan Liu, Yunhai Tong, Lizhuang Ma, Liqing Zhang
2021 arXiv   pre-print
In particular, we present temporal Transformer to aggregate both the spatial object queries and the feature memories of each frame.  ...  In this paper, we present TransVOD, an end-to-end video object detection model based on a spatial-temporal Transformer architecture.  ...  Our core idea is to aggregate both the spatial object queries and the memory encodings in each frame via Temporal Transformers.  ... 
arXiv:2105.10920v1 fatcat:gn2nnrqb7vhs3ml4xfxpgpqxwe

Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation [article]

Anirudh S Chakravarthy, Won-Dong Jang, Zudi Lin, Donglai Wei, Song Bai, Hanspeter Pfister
2021 arXiv   pre-print
Video instance segmentation aims to detect, segment, and track objects in a video. Current approaches extend image-level segmentation algorithms to the temporal domain.  ...  This allows our network to refocus on missing objects using box predictions from the neighbouring frame, thereby overcoming missing detections.  ...  Second, by propagating object masks through an inter-frame attention mechanism, we generate temporally coherent and spatially accurate mask tracks.  ... 
arXiv:2111.07529v3 fatcat:wqxl6izsrvft3fyc4p6gzfvnpa

Dual Temporal Memory Network for Efficient Video Object Segmentation [article]

Kaihua Zhang, Long Wang, Dong Liu, Bo Liu, Qingshan Liu, Zhu Li
2020 arXiv   pre-print
The short-term memory sub-network models the fine-grained spatial-temporal interactions between local regions across neighboring frames in video via a graph-based learning framework, which can well preserve  ...  Our network consists of two temporal sub-networks including a short-term memory sub-network and a long-term memory sub-network.  ...  The network includes three key components: (a) A short-term memory sub-network to capture the spatial-temporal consistency of local regions over time; (b) A long-term memory sub-network to model the evolution  ... 
arXiv:2003.06125v1 fatcat:gvspectsebewra5g5iusnrjydu

Real-time cooperative multi-target tracking by communicating active vision agents

N. Ukita, T. Matsuyama
2003 Sixth International Conference of Information Fusion, 2003. Proceedings of the  
All AVAs cooperatively track their target objects by dynamically exchanging object information with each other.  ...  This network is not a special closed network (e.g., PC cluster) but an open network.  ...  As we can see, the virtual synchronization helps both spatial and temporal object identifications, especially in the case of bad network conditions.  ... 
doi:10.1109/icif.2003.177480 fatcat:i3yb5xqagnh7jdtv6yommup7qy

Real-time cooperative multi-target tracking by communicating active vision agents

Norimichi Ukita, Takashi Matsuyama
2005 Computer Vision and Image Understanding  
All AVAs cooperatively track their target objects by dynamically exchanging object information with each other.  ...  This network is not a special closed network (e.g., PC cluster) but an open network.  ...  As we can see, the virtual synchronization helps both spatial and temporal object identifications, especially in the case of bad network conditions.  ... 
doi:10.1016/j.cviu.2004.07.004 fatcat:rey66yzdyrbydn5wjn2ecvnbpy

Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition [article]

Unaiza Ahsan, Rishi Madhok, Irfan Essa
2018 arXiv   pre-print
Recent self-supervised approaches have used spatial context [9, 34] as well as temporal coherency [32] but a combination of the two requires extensive preprocessing such as tracking objects through millions  ...  We propose a self-supervised learning method to jointly reason about spatial and temporal context for video recognition.  ...  This work attempts to combine spatial and temporal context but requires preprocessing to discover the tracked object patches.  ... 
arXiv:1808.07507v1 fatcat:pddkk2qnpvc4xm5jf3z5ga2hvi

Real-time multi-target tracking by cooperative distributed active vision agents

Norimichi Ukita, Takashi Matsuyama
2002 Proceedings of the first international joint conference on Autonomous agents and multiagent systems part 2 - AAMAS '02  
All AVAs cooperatively track their target objects by dynamically interacting with each other.  ...  Experimental results demonstrate that AVAs cooperatively track their target objects in real-time while adaptively changing their roles.  ...  As we can see, the virtual synchronization helps both spatial and temporal object identifications, especially in the case of bad network conditions.  ... 
doi:10.1145/544862.544936 dblp:conf/atal/UkitaM02 fatcat:l55llufxufavzg3iifmj32hnoi

Real-time multi-target tracking by cooperative distributed active vision agents

Norimichi Ukita, Takashi Matsuyama
2002 Proceedings of the first international joint conference on Autonomous agents and multiagent systems part 2 - AAMAS '02  
All AVAs cooperatively track their target objects by dynamically interacting with each other.  ...  Experimental results demonstrate that AVAs cooperatively track their target objects in real-time while adaptively changing their roles.  ...  As we can see, the virtual synchronization helps both spatial and temporal object identifications, especially in the case of bad network conditions.  ... 
doi:10.1145/544932.544936 fatcat:66b7bkqqbfeq7ca4itgesf6s2m

Memory and Space: Towards an Understanding of the Cognitive Map

D. Schiller, H. Eichenbaum, E. A. Buffalo, L. Davachi, D. J. Foster, S. Leutgeb, C. Ranganath
2015 Journal of Neuroscience  
, temporal, and associational context.  ...  Some researchers argue that the hippocampus plays a broad role in episodic and declarative memory, whereas others argue for a specific role in the creation of spatial cognitive maps and navigation.  ...  organized by their temporal sequence into a representation of a particular spatial memory.  ... 
doi:10.1523/jneurosci.2618-15.2015 pmid:26468191 pmcid:PMC6608181 fatcat:ivtvxcbpcrfh7kcrubk2dss4te

2019 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 29

2019 IEEE transactions on circuits and systems for video technology (Print)  
., +, TCSVT Dec. 2019 3673-3686 Video Saliency Prediction Based on Spatial-Temporal Two-Stream Network.  ...  Zhang, L., +, TCSVT May 2019 1339-1349 Video Saliency Prediction Based on Spatial-Temporal Two-Stream Network.  ... 
doi:10.1109/tcsvt.2019.2959179 fatcat:2bdmsygnonfjnmnvmb72c63tja

Behavioral functions of the CA3 subregion of the hippocampus

R. P. Kesner
2007 Learning & memory (Cold Spring Harbor, N.Y.)  
The CA3a,b also supports retrieval of short-term memory information based on a spatial pattern completion process.  ...  These are tasks that have been assumed to reflect the operations of episodic memory and require interactions between CA3a,b and the dentate gyrus via mossy fiber inputs into the CA3a,b.  ...  from the currently processed item via a chunking process and thus providing for a temporal-spatial context, suggesting that the dorsal CA1 can be thought of as performing temporal pattern completion for  ... 
doi:10.1101/lm.688207 pmid:18007020 fatcat:ombcnh64ajc55kaqu2jzycbepe

Real-time multitarget tracking by a cooperative distributed vision system

T. Matsuyama, N. Ukita
2002 Proceedings of the IEEE  
All AVAs cooperatively track their target objects by dynamically exchanging object information with each other.  ...  With this cooperative tracking capability, the system as a whole can track multiple moving objects persistently even under complicated dynamic environments in the real world.  ...  After an agency is generated, the agency manager repeats the spatial and temporal object identifications for cooperative tracking [ Fig. 14(a) ].  ... 
doi:10.1109/jproc.2002.801442 fatcat:zpn53xrtgbcivbanm6ou3rxioe
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