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Lucid Data Dreaming for Video Object Segmentation [article]

Anna Khoreva, Rodrigo Benenson, Eddy Ilg, Thomas Brox, Bernt Schiele
2019 arXiv   pre-print
Instead of using large training sets hoping to generalize across domains, we generate in-domain training data using the provided annotation on the first frame of each video to synthesize ("lucid dream"  ...  This changes the mindset regarding how many training samples and general "objectness" knowledge are required for the video object segmentation task.  ...  We propose "lucid data dreaming", an automated approach to synthesize training data for the convnet-based pixel-level video object segmentation that leads to top results for both single and multiple object  ... 
arXiv:1703.09554v5 fatcat:yzlqocshgfhmxe3rxvenqp2m6y

Lucid Data Dreaming for Video Object Segmentation

Anna Khoreva, Rodrigo Benenson, Eddy Ilg, Thomas Brox, Bernt Schiele
2019 International Journal of Computer Vision  
This changes the mindset regarding how many training samples and general "objectness" knowledge are required for the video object segmentation task.  ...  Our approach is suitable for both single and multiple object segmentation.  ...  We propose "lucid data dreaming", an automated approach to synthesize training data for the convnetbased pixel-level video object segmentation that leads to top results for both single and multiple object  ... 
doi:10.1007/s11263-019-01164-6 fatcat:oavuhac5xjgyzigyt7iqovlz5u

Symmetry Encoder-Decoder Network with Attention Mechanism for Fast Video Object Segmentation

Mingyue Guo, Dejun Zhang, Jun Sun, Yiqi Wu
2019 Symmetry  
In this work, to address this issue, we propose a symmetry encoder-decoder network with the attention mechanism for video object segmentation (SAVOS) requiring only one forward pass to segment the target  ...  object in a video.  ...  This decline demonstrated that the "lucid dream" data augmentation was useful to improve the performance.  ... 
doi:10.3390/sym11081006 fatcat:sz6p6bgut5bcpevp64nqm45wwq

Contextual Guided Segmentation Framework for Semi-supervised Video Instance Segmentation [article]

Trung-Nghia Le and Tam V. Nguyen and Minh-Triet Tran
2021 arXiv   pre-print
In this paper, we propose Contextual Guided Segmentation (CGS) framework for video instance segmentation in three passes.  ...  For human instance, we develop skeleton-guided segmentation in a frame along with object flow to correct and refine the result across frames.  ...  We also thank NVIDIA and AIOZ Pte Ltd for the support of GPU and computing infrastructure.  ... 
arXiv:2106.03330v1 fatcat:2gku7u36lne3dp3zvauquexwjq

Spatiotemporal CNN for Video Object Segmentation [article]

Kai Xu, Longyin Wen, Guorong Li, Liefeng Bo, Qingming Huang
2019 arXiv   pre-print
Specifically, the temporal coherence branch pretrained in an adversarial fashion from unlabeled video data, is designed to capture the dynamic appearance and motion cues of video sequences to guide object  ...  In this way, the spatial segmentation branch is enforced to gradually concentrate on object regions. These two branches are jointly fine-tuned on video segmentation sequences in an end-to-end manner.  ...  For a fair comparison, we use the same parameter settings except for the specific declaration. Lucid dream augmentation.  ... 
arXiv:1904.02363v1 fatcat:mmzxevx4hrcdzfnllksl6pyrjy

Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation [article]

Ye Wang, Jongmoo Choi, Yueru Chen, Qin Huang, Siyang Li, Ming-Sui Lee, C.-C. Jay Kuo
2018 arXiv   pre-print
One major technique debt in video object segmentation is to label the object masks for training instances.  ...  As a result, we propose to prepare inexpensive, yet high quality pseudo ground truth corrected with motion cue for video object segmentation training.  ...  We generate augmentation of the first frame using Lucid Data Dreaming approach.  ... 
arXiv:1812.05206v1 fatcat:frprtbqbqbeofd34mzjkiozqma

Exploring the Combination of PReMVOS, BoLTVOS and UnOVOST for the 2019 YouTube-VOS Challenge

Jonathon Luiten, Paul Voigtlaender, Bastian Leibe
2019 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)  
Video Object Segmentation is the task of tracking and segmenting objects in a video given the first-frame mask of objects to be tracked.  ...  In this paper we explore how these three different approaches can be combined into a novel Video Object Segmentation algorithm.  ...  For each first-frame mask, we fine-tune Box2Seg for 300 steps and then segment each conditional detection for this object. To save time, we do not use Lucid data dreaming augmentations. Tracklets.  ... 
doi:10.1109/iccvw.2019.00087 dblp:conf/iccvw/LuitenVL19 fatcat:sf53s33mhvhspbnm77hcgcnza4

PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation [article]

Jonathon Luiten, Paul Voigtlaender, Bastian Leibe
2018 arXiv   pre-print
Towards this goal, we present the PReMVOS algorithm (Proposal-generation, Refinement and Merging for Video Object Segmentation).  ...  We address semi-supervised video object segmentation, the task of automatically generating accurate and consistent pixel masks for objects in a video sequence, given the first-frame ground truth annotations  ...  We use the Lucid Data Dreaming method proposed in [15] but only generate single images (not image pairs).  ... 
arXiv:1807.09190v2 fatcat:yhw4l5nb5fg6tphdbvwwbxj2bi

Video game play as nightmare protection: A preliminary inquiry with military gamers

Jayne Gackenbach, Evelyn Ellerman, Christie Hall
2011 Dreaming (New York, N.Y.)  
Dream content analysis was conducted using threat simulation, war content and lucid/control/gaming content.  ...  Soldiers who play video games to varying degrees were solicited to fill out a survey on dreams and gaming.  ...  The final set of dream coding completed was for lucid and control type dream content, as well as for gaming content.  ... 
doi:10.1037/a0024972 fatcat:tsftgcpcfbew5irainyr2gmlyq

REM sleep respiratory behaviours match mental content in narcoleptic lucid dreamers

Delphine Oudiette, Pauline Dodet, Nahema Ledard, Emilie Artru, Inès Rachidi, Thomas Similowski, Isabelle Arnulf
2018 Scientific Reports  
It was legally sponsored by ADOREPS, a non-profit research association for research in pneumology and sleep.  ...  Incongruence between subjective behaviours and objective evidence. There were 4 instances of coded lucid dreams without any visible respiratory adaptation.  ...  report with its corresponding segment in the sleep recording.  ... 
doi:10.1038/s41598-018-21067-9 pmid:29422603 pmcid:PMC5805737 fatcat:wgr44bta6zh3xfzddel5bj6aee

Lucid Dreaming in Narcolepsy

Pauline Dodet, Mario Chavez, Smaranda Leu-Semenescu, Jean-Louis Golmard, Isabelle Arnulf
2015 Sleep  
Conclusion: Narcoleptics have a high propensity for lucid dreaming without differing in REM sleep characteristics from people without narcolepsy.  ...  Objective: To evaluate the frequency, determinants and sleep characteristics of lucid dreaming in narcolepsy Settings: University hospital sleep disorder unit Design: Case-control study Participants: Consecutive  ...  Data are presented as the mean ± standard deviation.  ... 
doi:10.5665/sleep.4516 pmid:25348131 pmcid:PMC4335518 fatcat:xho6lyrcirfshp7ywp5wm5psmm

An End-to-End Edge Aggregation Network for Moving Object Segmentation

Prashant W. Patil, Kuldeep M. Biradar, Akshay Dudhane, Subrahmanyam Murala
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Moving object segmentation in videos (MOS) is a highly demanding task for security-based applications like automated outdoor video surveillance.  ...  The performance of the proposed network is evaluated with different configurations like disjoint, cross-data, and global training-testing techniques.  ...  Khoreva et al. [15] proposed data augmentation technique i.e. lucid data dreaming for semi-supervised video object segmentation (VOS).  ... 
doi:10.1109/cvpr42600.2020.00817 dblp:conf/cvpr/PatilBDM20 fatcat:xnzfqkpwi5dtrcemknvjmygmsi

LSMVOS: Long-Short-Term Similarity Matching for Video Object [article]

Zhang Xuerui, Yuan Xia
2020 arXiv   pre-print
Objective Semi-supervised video object segmentation refers to segmenting the object in subsequent frames given the object label in the first frame.  ...  By combining the long-term matching module with the short-term matching module, the whole network can achieve efficient video object segmentation without online fine tuning  ...  This method is developed on the basis of Lucid Data Dreaming for synthetic video frames, proposed by A.  ... 
arXiv:2009.00771v1 fatcat:3l2bjjz7pnfwndvemaktx7l7pi

Real-Time Dialogue between Experimenters and Dreamers During rem Sleep

Karen Konkoly, Kristoffer Appel, Emma Chabani, Alexander Y. Mironov, Anastasia Mangiaruga, Jarrod Gott, Remington Mallett, Bruce Caughran, Sarah Witkowski, Nathan Whitmore, Jonathan Berent, Frederik Weber (+9 others)
2020 Social Science Research Network  
and distorted d Our methods allow for two-way communication with individuals during a lucid dream d For a proof-of-concept demonstration, we presented math problems and yes-no questions d Dreamers answered  ...  Some had minimal prior experience with lucid dreaming, others were frequent lucid dreamers, and one was a patient with narcolepsy who had frequent lucid dreams.  ...  Upon awakening, the participant reported dreaming about his favorite video game: ''I was in a parking lot at night.then suddenly it was daytime and I was in the video game..  ... 
doi:10.2139/ssrn.3606772 fatcat:yn3cpt22wbgihhe763mc6lbhsa

The 2017 DAVIS Challenge on Video Object Segmentation [article]

Jordi Pont-Tuset and Federico Perazzi and Sergi Caelles and Pablo Arbeláez and Alex Sorkine-Hornung and Luc Van Gool
2018 arXiv   pre-print
We present the 2017 DAVIS Challenge on Video Object Segmentation, a public dataset, benchmark, and competition specifically designed for the task of video object segmentation.  ...  The DAVIS Challenge follows up on the recent publication of DAVIS (Densely-Annotated VIdeo Segmentation), which has fostered the development of several novel state-of-the-art video object segmentation  ...  The authors gratefully acknowledge support by armasuisse, and thank NVIDIA Corporation for donating the GPUs used in this project.  ... 
arXiv:1704.00675v3 fatcat:5fqbhig3kfgepcomwys2obb6qa
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