Filters








371 Hits in 7.3 sec

Context-Patch Face Hallucination Based on Thresholding Locality-constrained Representation and Reproducing Learning [article]

Junjun Jiang, Yi Yu, Suhua Tang, Jiayi Ma, Akiko Aizawa, Kiyoharu Aizawa
2018 arXiv   pre-print
To this end, this study incorporates the contextual information of image patch and proposes a powerful and efficient context-patch based face hallucination approach, namely Thresholding Locality-constrained  ...  Representation and Reproducing learning (TLcR-RL).  ...  patch reconstruction method based on thresholding locality-constrained representation.  ... 
arXiv:1809.00665v2 fatcat:fgdwkt7kezfofefaxhnmewslhu

Face hallucination based on cluster consistent dictionary learning

Minqi Li, Xiangjian He, Kin‐Man Lam, Kaibing Zhang, Junfeng Jing
2021 IET Image Processing  
This paper, proposes a novel example-based face hallucination method, based on cluster consistent dictionary learning with the assumption that human faces have similar facial structures.  ...  Then, the training patches are clustered according their labels and textures. The cluster consistent dictionary is learned to represent the low-resolution patches and the high-resolution patches.  ...  TLcR-RL uses context information and reproducing learning by adding the hallucinated HR face image to the training set.  ... 
doi:10.1049/ipr2.12269 fatcat:bfncysrggbfrdktz7ayc5rxg6u

Discriminative Face Hallucination via Locality-Constrained and Category Embedding Representation

Licheng Liu, Rushi Lan, Yaonan Wang
2020 IEEE Transactions on Systems, Man & Cybernetics. Systems  
This article proposes a locality-constrained and category embedding representation (LCER) method to super-resolve face image in a supervised manner by embedding the label information in data representation  ...  The proposed LCER incorporates the locality prior and category information into one unified framework, which aims to learn both the advantages of locality in preserving the true typologic structure of  ...  [30] presented a thresholding LcR with the strategy of reproducing learning (TLcR-RL) for face hallucination, in which the newly reconstructed face was added back to the training dataset to strengthen  ... 
doi:10.1109/tsmc.2020.2965572 fatcat:cttonyzw5rbglkpsjjm7gsba54

Teacher-Student Adversarial Depth Hallucination to Improve Face Recognition [article]

Hardik Uppal, Alireza Sepas-Moghaddam, Michael Greenspan, Ali Etemad
2021 arXiv   pre-print
The student, which consists of two generators (one shared with the teacher) and a discriminator, learns from new RGB data with no available paired depth information, for improved generalization.  ...  The fully trained shared generator can then be used in runtime to hallucinate depth from RGB for downstream applications such as face recognition.  ...  The authors would like to thank Irdeto Canada Corporation and the Natural Sciences and Engineering Research Council of Canada (NSERC) for funding this research.  ... 
arXiv:2104.02424v2 fatcat:ehycefwn5nht3crjtdqqv4fida

APRICOT: A Dataset of Physical Adversarial Attacks on Object Detection [article]

A. Braunegg, Amartya Chakraborty, Michael Krumdick, Nicole Lape, Sara Leary, Keith Manville, Elizabeth Merkhofer, Laura Strickhart, Matthew Walmer
2020 arXiv   pre-print
Physical adversarial attacks threaten to fool object detection systems, but reproducible research on the real-world effectiveness of physical patches and how to defend against them requires a publicly  ...  This dataset and the described experiments provide a benchmark for future research on the effectiveness of and defenses against physical adversarial objects in the wild.  ...  Acknowledgments We would like to thank Mikel Rodriguez, David Jacobs, Rama Chellappa, and Abhinav Shrivastava for helpful discussions and feedback on this work.  ... 
arXiv:1912.08166v2 fatcat:b3uekiyoinf6zl2skwgbp2sgg4

Deep Learning for Image Super-resolution: A Survey [article]

Zhihao Wang, Jian Chen, Steven C.H. Hoi
2020 arXiv   pre-print
This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches.  ...  Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques.  ...  [30] focus on face image SR and introduce a face alignment network (FAN) to constrain the consistency of facial landmarks.  ... 
arXiv:1902.06068v2 fatcat:uequ4heufbcmjojclu2md3xh6m

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis [article]

Mehdi S. M. Sajjadi and Bernhard Schölkopf and Michael Hirsch
2017 arXiv   pre-print
Extensive experiments on a number of datasets show the effectiveness of our approach, yielding state-of-the-art results in both quantitative and qualitative benchmarks.  ...  As a result, algorithms minimizing these metrics tend to produce over-smoothed images that lack high-frequency textures and do not look natural despite yielding high PSNR values.  ...  in a highly constrained setting for the task of face hallucination [62] .  ... 
arXiv:1612.07919v2 fatcat:smk4uaeahnavjj5acs5yhnrlku

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

Shunsuke Saito, Tomas Simon, Jason Saragih, Hanbyul Joo
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Recent advances in image-based 3D human shape estimation have been driven by the significant improvement in representation power afforded by deep neural networks.  ...  A coarse level observes the whole image at lower resolution and focuses on holistic reasoning.  ...  We base our method on the recently introduced Pixel-Aligned Implicit Function (PIFu) representation [35] .  ... 
doi:10.1109/cvpr42600.2020.00016 dblp:conf/cvpr/SaitoSSJ20 fatcat:qzcixs3fujfz7kz3jxpghrfuu4

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization [article]

Shunsuke Saito, Tomas Simon, Jason Saragih, Hanbyul Joo
2020 arXiv   pre-print
Recent advances in image-based 3D human shape estimation have been driven by the significant improvement in representation power afforded by deep neural networks.  ...  A coarse level observes the whole image at lower resolution and focuses on holistic reasoning.  ...  We base our method on the recently introduced Pixel-Aligned Implicit Function (PIFu) representation [35] .  ... 
arXiv:2004.00452v1 fatcat:yf63rox7hbfqpfvtrjxfawe5qq

Non-Parametric Neural Style Transfer [article]

Nicholas Kolkin
2021 arXiv   pre-print
I will begin by proposing novel definitions of style and content based on optimal transport and self-similarity, and demonstrating how a style transfer algorithm based on these definitions generates outputs  ...  Finally I will describe a framework inspired by both modern neural style transfer algorithms and traditional patch-based synthesis approaches which is fast, general, and offers state-of-the-art visual  ...  on the stylized output and the original style to learn a content-invariant representations of style.  ... 
arXiv:2108.12847v1 fatcat:v3mtlfi45vccjnh4r2pzuf4ntu

2020 Index IEEE Transactions on Cybernetics Vol. 50

2020 IEEE Transactions on Cybernetics  
., and Gao, H., Reference Trajectory Reshaping Optimi-zation and Control of Robotic Exoskeletons for Human-Robot Co-Manipulation; TCYB Aug. 2020 3740-3751 Wu, X., Jiang, B., Yu, K., Miao, c., and Chen,  ...  ., +, TCYB July 2020 3409-3422 Context-Patch Face Hallucination Based on Thresholding Locality-Con- strained Representation and Reproducing Learning.  ...  Wang, H., +, TCYB April 2020 1541-1555 Context-Patch Face Hallucination Based on Thresholding Locality-Con- strained Representation and Reproducing Learning.  ... 
doi:10.1109/tcyb.2020.3047216 fatcat:5giw32c2u5h23fu4drupnh644a

Neural Neighbor Style Transfer [article]

Nicholas Kolkin, Michal Kucera, Sylvain Paris, Daniel Sykora, Eli Shechtman, Greg Shakhnarovich
2022 arXiv   pre-print
Our approach is based on explicitly replacing neural features extracted from the content input (to be stylized) with those from a style exemplar, then synthesizing the final output based on these rearranged  ...  We propose Neural Neighbor Style Transfer (NNST), a pipeline that offers state-of-the-art quality, generalization, and competitive efficiency for artistic style transfer.  ...  In the arbitrary style transfer setting, these approaches performs better than patch-based techniques, nevertheless, methods that use a content and style loss, both based on VGG features, face a fundamental  ... 
arXiv:2203.13215v1 fatcat:crrccbvxkzbihh6w74wyv3o2tq

A Stochastic Grammar of Images

Song-Chun Zhu, David Mumford
2006 Foundations and Trends in Computer Graphics and Vision  
It also combines the structure-based and appearance based methods in the vision literature.  ...  The probabilistic model defined on this And-Or graph representation can be learned from a relatively small training set per category and then sampled through Monte Carlo simulation to synthesize a large  ...  Stuart Geman, Yingnian Wu, Harry Shum, Alan Yuille, and Joachim Buhmann for their extensive discussions and helpful comments. The first author also thanks many students at UCLA  ... 
doi:10.1561/0600000018 fatcat:4gicslrfufabratzlxeiz275nm

FACE RECOGNITION FROM VIDEO: A REVIEW

JEREMIAH R. BARR, KEVIN W. BOWYER, PATRICK J. FLYNN, SOMA BISWAS
2012 International journal of pattern recognition and artificial intelligence  
Driven by key law enforcement and commercial applications, research on face recognition from video sources has intensified in recent years.  ...  We also draw connections between the ways in which humans and current algorithms recognize faces.  ...  The opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of our sponsors.  ... 
doi:10.1142/s0218001412660024 fatcat:xztw7hmpsjacbogyn22axiq4tq

Deformation-Aware Unpaired Image Translation for Pose Estimation on Laboratory Animals

Siyuan Li, Semih Gunel, Mirela Ostrek, Pavan Ramdya, Pascal Fua, Helge Rhodin
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
We compare our approach with existing domain transfer methods and demonstrate improved pose estimation accuracy on Drosophila melanogaster (fruit fly), Caenorhabditis elegans (worm) and Danio rerio (zebrafish  ...  ), without requiring any manual annotation on the target domain and despite using simplistic off-the-shelf animal characters for simulation, or simple geometric shapes as models.  ...  Acknowlegments SG, PR, and PF acknowledge support from an EPFL SV iPhD grant  ... 
doi:10.1109/cvpr42600.2020.01317 dblp:conf/cvpr/LiGORFR20 fatcat:fxadztnixfhfviyx6hhe2qxgfu
« Previous Showing results 1 — 15 out of 371 results