Filters








49,543 Hits in 3.2 sec

Bilinear models of natural images

Bruno A. Olshausen, Charles Cadieu, Jack Culpepper, David K. Warland, Bernice E. Rogowitz, Thrasyvoulos N. Pappas, Scott J. Daly
2007 Human Vision and Electronic Imaging XII  
In this paper, we describe how bilinear image models can be used to learn independent representations of the invariances, and their transformations, in natural image sequences.  ...  These models provide the foundation for learning higher-order feature representations that could serve as models of higher stages of processing in the cortex, in addition to having practical merit for  ...  ACKNOWLEDGMENTS We thank Kilian Koepsell for useful discussions during the preparation of this manuscript. Work supported by NGA grant MCA 015894-UCB and NSF grant IIS-06-25223 to B.A.O.  ... 
doi:10.1117/12.715515 dblp:conf/hvei/OlshausenCCW07 fatcat:xe35pjhiubfubigtdgnau534xa

Bilinear Sparse Coding for Invariant Vision

David B. Grimes, Rajesh P. N. Rao
2005 Neural Computation  
We show that from an arbitrary set of natural images, the algorithm produces oriented basis filters that can simultaneously represent features in an image and their transformations.  ...  We describe an unsupervised algorithm for learning both localized features and their transformations directly from images using a sparse bilinear generative model.  ...  Bilinear Sparse Coding of Natural Images. Experimental results are analyzed as follows.  ... 
doi:10.1162/0899766052530893 pmid:15563747 fatcat:byywmfsk3bfpxh4c53tbvprfmm

Colour Restoration of Image Obtained from CCD Sensor Directly

Jun Luo, Ying Chen
2014 Cybernetics and Information Technologies  
the color of original image.  ...  However, the hues of adjacent pixels change abruptly by the bilinear interpolation, therefore, we use smooth hue transition interpolation to enhance the edge of original image, and finally we identify  ...  The results show that the GB model is right for interpolation algorithm, the others are not correct, because they can not restore the natural colour of the key.  ... 
doi:10.2478/cait-2014-0021 fatcat:t234mi6vnzexdbovuqfe6oppae

X-Linear Attention Networks for Image Captioning [article]

Yingwei Pan and Ting Yao and Yehao Li and Tao Mei
2020 arXiv   pre-print
Furthermore, we present X-Linear Attention Networks (dubbed as X-LAN) that novelly integrates X-Linear attention block(s) into image encoder and sentence decoder of image captioning model to leverage higher  ...  Nevertheless, there has not been evidence in support of building such interactions concurrently with attention mechanism for image captioning.  ...  Introduction Image captioning is the task of automatically producing a natural-language sentence to describe the visual content of an image.  ... 
arXiv:2003.14080v1 fatcat:ii7jfpw7jjgchjk3qz6a55v7zu

Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance under Natural Illumination and Non-Lambertian Reflectance

Shireen Y. Elhabian, Aly A. Farag
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
Representing images as matrices further lessen the number of parameters to be estimated to define a bilinear projection which maps the image sample to a lowerdimensional bilinear subspace.  ...  In this paper, we propose an analytic formulation for low-dimensional subspace construction in which shading cues lie while preserving the natural structure of an image sample.  ...  This highlights the benefit of the proposed bilinear appearance model in terms of robustness against noise.  ... 
doi:10.1109/cvpr.2013.190 dblp:conf/cvpr/ElhabianF13 fatcat:bhbcvczzrffotkscdva6lx75mq

Real World Robustness from Systematic Noise [article]

Yan Wang, Yuhang Li, Ruihao Gong
2021 arXiv   pre-print
More specifically, we find the trained neural network classifier can be fooled by inconsistent implementations of image decoding and resize.  ...  These noises are model-agnostic and may cause perceptible perturbation. Natural noises such as Snow noise and Frost noise can measure the robustness of a model in the wild.  ...  To solve this problem, a natural way is to make the model "see" all kinds of decoders and resize methods during the training process.  ... 
arXiv:2109.00864v1 fatcat:phex4fgszng6rbjkrlpludbqee

Large-Scale Fine-Grained Bird Recognition Based on a Triplet Network and Bilinear Model

Zhicheng Zhao, Ze Luo, Jian Li, Kaihua Wang, Bingying Shi
2018 Applied Sciences  
The experimental results confirm the high generalization ability of our model in fine-grained image classification.  ...  We propose a model based on a triple network and bilinear methods for fine-grained bird identification.  ...  A bilinear CNN model that performs local-area detection and feature extraction using two networks was proposed in [14] . Birds are an important part of natural ecosystem.  ... 
doi:10.3390/app8101906 fatcat:aujspgumknbblksvlilha5zgum

Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding

Akira Fukui, Dong Huk Park, Daylen Yang, Anna Rohrbach, Trevor Darrell, Marcus Rohrbach
2016 Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing  
This model outperforms the state-of-the-art on the Visual7W dataset and the VQA challenge.  ...  We consistently show the benefit of MCB over ablations without MCB.  ...  Acknowledgments We would like to thank Yang Gao and Oscar Beijbom for helpful discussions about Compact Bilinear Pooling.  ... 
doi:10.18653/v1/d16-1044 dblp:conf/emnlp/FukuiPYRDR16 fatcat:x5tuyaqoujhzxpfxcyvkqbmqkm

Visualizing and Understanding Deep Texture Representations [article]

Tsung-Yu Lin, Subhransu Maji
2016 arXiv   pre-print
Finally, we show preliminary results on how a unified parametric model of texture analysis and synthesis can be used for attribute-based image manipulation, e.g. to make an image more swirly, honeycombed  ...  This work conducts a systematic evaluation of recent CNN-based texture descriptors for recognition and attempts to understand the nature of invariances captured by these representations.  ...  The orderless nature of the texture descriptor is essential to produce such sharp images.  ... 
arXiv:1511.05197v2 fatcat:x3tnmjrh4banncar7p5kpxprba

Visualizing and Understanding Deep Texture Representations

Tsung-Yu Lin, Subhransu Maji
2016 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Finally, we show preliminary results on how a unified parametric model of texture analysis and synthesis can be used for attribute-based image manipulation, e.g. to make an image more swirly, honeycombed  ...  This work conducts a systematic evaluation of recent CNN-based texture descriptors for recognition and attempts to understand the nature of invariances captured by these representations.  ...  The orderless nature of the texture descriptor is essential to produce such sharp images.  ... 
doi:10.1109/cvpr.2016.305 dblp:conf/cvpr/LinM16 fatcat:bqrc5ffozjebfld7r563chgvme

Bilinear deep learning for image classification

Sheng-hua Zhong, Yan Liu, Yang Liu
2011 Proceedings of the 19th ACM international conference on Multimedia - MM '11  
This paper proposes a novel deep learning model called bilinear deep belief network (BDBN) for image classification.  ...  To preserve the natural tensor structure of the image data, a novel deep architecture with greedy layer-wise reconstruction and global fine-tuning is proposed.  ...  Figure 8 . 8 Sample images from the Urban & Natural Scene. Figure 9 . 9 Limitation of image classification via visual similarity. (a) A representative image of "Street".  ... 
doi:10.1145/2072298.2072344 dblp:conf/mm/ZhongLL11 fatcat:jwm3dglmzzfkzkxhh2xlxfs6be

User Conditional Hashtag Prediction for Images

Emily Denton, Jason Weston, Manohar Paluri, Lubomir Bourdev, Rob Fergus
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
We apply these models to a large dataset of de-identified Facebook posts and demonstrate that modeling the user can significantly improve the tag prediction quality over current state-of-the-art methods  ...  We explore two ways of combining these heterogeneous features into a learning framework: (i) simple concatenation; and (ii) a 3-way multiplicative gating, where the image model is conditioned on the user  ...  We now describe each of these models in detail. Bilinear Model The bilinear embedding model [17] does not incorporate any user information into the image embedding function.  ... 
doi:10.1145/2783258.2788576 dblp:conf/kdd/DentonWPBF15 fatcat:3wnrc5zijbhj7fwayk5ackyc4u

Bilinear deep learning for image classification

Shenghua Zhong, Yan Liu, Yang Liu
2011 Proceedings of the 19th ACM international conference on Multimedia - MM '11  
This paper proposes a novel deep learning model called bilinear deep belief network (BDBN) for image classification.  ...  To preserve the natural tensor structure of the image data, a novel deep architecture with greedy layer-wise reconstruction and global fine-tuning is proposed.  ...  Figure 8 . 8 Sample images from the Urban & Natural Scene. Figure 9 . 9 Limitation of image classification via visual similarity. (a) A representative image of "Street".  ... 
doi:10.1145/2072298.2072505 dblp:conf/mm/ZhongLL11a fatcat:yiqrng6v25dz3aw2c6azxmnypm

Bilinear factorisation for facial expression analysis and synthesis

B. Abboud, F. Davoine
2005 IEE Proceedings - Vision Image and Signal Processing  
Results are compared to the ones obtained for the same training and test images using classification of the expression factors extracted by bilinear factorization.  ...  Although active appearance models and bilinear modelling are not new concepts, the main contribution of this paper consists in combining both techniques to improve facial expression recognition and synthesis  ...  In this perspective, we choose to model the mapping from expression and identity parameters to natural faces using a bilinear factorization model.  ... 
doi:10.1049/ip-vis:20045060 fatcat:t73sh5ccyjgotprjpwm7ghmtgq

Bilinear image translation for temporal analysis of photo collections

Theophile Dalens, Mathieu Aubry, Josef Sivic
2019 IEEE Transactions on Pattern Analysis and Machine Intelligence  
We apply our model to a challenging collection of more than 13,000 cars manufactured between 1920 and 2000 [4] and a dataset of high school yearbook portraits from 1930 to 2009 [5] .  ...  To isolate and transfer time dependent appearance variations, we introduce a new trainable bilinear factor separation module.  ...  be distinguished from natural images.  ... 
doi:10.1109/tpami.2019.2950317 pmid:31675318 fatcat:tl3l3w2aqvb4ff5ifnyudxyj5a
« Previous Showing results 1 — 15 out of 49,543 results