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Discovering Style Trends through Deep Visually Aware Latent Item Embeddings 31

Discovering Style Trends through Deep Visually Aware Latent ...

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Iqbal, Murium Kovac, Adair Aryafar, Kamelia Overstock Com Midvale UT 84047 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

In this paper, we explore Latent Dirichlet Allocation (LDA) [1] and Polylingual Latent Dirichlet Allocation (PolyLDA) [6], as a means to discover trending styles in Overstock 1 from deep visual semantic features transferred from a pretrained convolutional neural network and text-based item attributes. To utilize deep visual semantic features in conjunction with LDA, we develop a method for creating a bag of words representation of unrolled image vectors. By viewing the channels within the convolutional layers of a Resnet-50 [2] as being representative of a word, we can index these activations to create visual documents. We then train LDA over these documents to discover the latent style in the images. We also incorporate text-based data with PolyLDA, where each representation is viewed as an independent language attempting to describe the same style. The resulting topics are shown to be excellent indicators of visual style across our platform.

关键词： Visualization Semantics Image color analysis Shape Vocabulary Data models computer vision

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Geometry-aware Traffic Flow Analysis by Detection and Tracking 31

Geometry-aware Traffic Flow Analysis by Detection and Tracki...

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Shi, Honghui Wang, Zhonghao Zhang, Yang Wang, Xinchao Huang, Thomas UIUC IFP Grp Beckman Inst Champaign IL 61820 USA IBM Res San Jose CA 95120 USA Stevens Inst Technol Hoboken NJ 07030 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

In the second Nvidia AI City Challenge hosted in 2018, the traffic flow analysis challenge proposes an interest task that requires participants to predict the speed of vehicles on road from various traffic camera videos. We propose a simple yet effective method combing both learning based detection and geometric calibration based estimation. We use a learning based method to detect and track vehicles, and use a geometry based camera calibration method to calculate the speed of those vehicles. We achieve a perfect detection rate of target vehicles and a root mean square error (RMSE) of 6.6674 in predicting the vehicle speed, which rank us the third place in the competition.

关键词： Videos Roads Cameras Estimation Tracking computer vision Artificial intelligence

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A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders 31

A Generative Model For Zero Shot Learning Using Conditional ...

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Mishra, Ashish Reddy, Shiva Krishna Mittal, Anurag Murthy, Hema A. Indian Inst Technol Madras Chennai Tamil Nadu India

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language descriptions or attribute vectors of the classes are available. This setting is important in the real world since one may not be able to obtain images of all the possible classes at training. While previous approaches have tried to model the relationship between the class attribute space and the image space via some kind of a transfer function in order to model the image space correspondingly to an unseen class, we take a different approach and try to generate the samples from the given attributes, using a conditional variational autoencoder, and use the generated samples for classification of the unseen classes. By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes.

关键词： Semantics Training Image generation Decoding Visualization Data models computer vision

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Locally-Weighted Elastic Comparison of Planar Shapes 31

Locally-Weighted Elastic Comparison of Planar Shapes

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Strait, Justin Kurtek, Sebastian MacEachern, Steven Ohio State Univ Dept Stat Columbus OH 43210 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Registration of curves is a necessary component of statistical shape analysis. The goal of registration is to align collections of shapes so that common features are appropriately matched for further comparison and subsequent analyses. Traditional methods for registration typically rely on optimizing an energy functional over a set of appropriate shape-preserving transformations (i.e., rotations and re-parameterizations). These functionals typically rely on the standard L-2 metric. In certain applications, it may make sense to use a more flexible metric which can align shapes most preferably with respect to a local shape feature (i.e., a certain curve segment selected from the overall shape). In this work, we define a weighted shape metric which allows for emphasis on local shape features. Registration can be performed with respect to this metric. We demonstrate the registration procedure using simulated curves as well as real data, and show the dependence of the optimal rotation and re-parameterization on the specified weights, as well as the resulting deformation path from one shape to another.

关键词： Shape Measurement Silicon computer vision Standards Strain Beak

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Early Detection of Injuries in MLB Pitchers from Video

Early Detection of Injuries in MLB Pitchers from Video

引用

ieee/cvf conference on computer vision and pattern recognition workshops

作者： AJ Piergiovanni Michael S. Ryoo Department of Computer Science Indiana University

ISBN: (数字)9781728125060

ISBN: (纸本)9781728125077

Injuries are a major cost in sports. Teams spend millions of dollars every year on players who are hurt and unable to play, resulting in lost games, decreased fan interest and additional wages for replacement players. Modern convolutional neural networks have been successfully applied to many video recognition tasks. In this paper, we introduce the problem of injury detection/prediction in MLB pitchers and experimentally evaluate the ability of such convolutional models to detect and predict injuries in pitches only from video data. We conduct experiments on a large dataset of TV broadcast MLB videos of 20 different pitchers who were injured during the 2017 season. We experimentally evaluate the model's performance on each individual pitcher, how well it generalizes to new pitchers, how it performs for various injuries, and how early it can predict or detect an injury.

关键词： Injuries Videotapes Printed Circuit Board Device Component Early Diagnosis Players video data Sports

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Elastic Handling of Predictor Phase in Functional Regression Models 31

Elastic Handling of Predictor Phase in Functional Regression...

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Ahn, Kyungmin Tucker, J. Derek Wu, Wei Srivastava, Anuj Florida State Univ Dept Stat Tallahassee FL 32306 USA Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Functional variables serve important roles as predictors in a variety of pattern recognition and vision applications. Focusing on a specific subproblem, termed scalar-on-function regression, most current approaches adopt the standard L-2 inner product to form a link between functional predictors and scalar responses. These methods may perform poorly when predictor functions contain nuisance phase variability, i.e., predictors are temporally misaligned due to noise. While a simple solution could be to prealign predictors as a pre-processing step, before applying a regression model, this alignment is seldom optimal from the perspective of regression. We propose a new approach, termed elastic functional regression, where alignment is included in the regression model itself, and is performed in conjunction with the estimation of other model parameters. This model is based on a norm-preserving warping of predictors, not the standard time warping of functions, and provides better prediction in situations where the shape or the amplitude of the predictor is more useful than its phase. We demonstrate the effectiveness of this framework using simulated and stock market data.

关键词： Predictive models Measurement Data models Standards Shape Estimation pattern recognition

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Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

Adapting Image Super-Resolution State-of-the-arts and Learni...

引用

ieee/cvf conference on computer vision and pattern recognition workshops

作者： Chao Li Dongliang He Xiao Liu Yukang Ding Shilei Wen Department of Computer Vision Technology (VIS) Baidu Inc

ISBN: (数字)9781728125060

ISBN: (纸本)9781728125077

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks. However, there has been limited advancement in video super-resolution (VSR) due to the complex temporal patterns in videos. In this paper, we investigate how to adapt state-of-the-art methods of image super-resolution for video super-resolution. The proposed adapting method is straightforward. The information among successive frames is well exploited, while the overhead on the original image super-resolution method is negligible. Furthermore, we propose a learning-based method to ensemble the outputs from multiple super-resolution models. Our methods show superior performance and rank second in the NTIRE2019 Video Super-Resolution Challenge Track 1.

关键词： super-resolution Videotapes Arts Learning-based method

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Finding your Lookalike: Measuring Face Similarity Rather than Face Identity 31

Finding your Lookalike: Measuring Face Similarity Rather tha...

引用

ieee/cvf conference on computer vision and pattern recognition (CVPR)

作者： Sadovnik, Amir Gharbi, Wassim Thanh Vu Gallagher, Andrew Lafayette Coll Easton PA 18042 USA Google Res Mountain View CA USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Face images are one of the main areas of focus for computer vision, receiving on a wide variety of tasks. Although face recognition is probably the most widely researched, many other tasks such as kinship detection, facial expression classification and facial aging have been examined. In this work we propose the new, subjective task of quantifying perceived face similarity between a pair of faces. That is, we predict the perceived similarity between facial images, given that they are not of the same person. Although this task is clearly correlated with face recognition, it is different and therefore justifies a separate investigation. Humans often remark that two persons look alike, even in cases where the persons are not actually confused with one another. In addition, because face similarity is different than traditional image similarity, there are challenges in data collection and labeling, and dealing with diverging subjective opinions between human labelers. We present evidence that finding facial look-alikes and recognizing faces are two distinct tasks. We propose a new dataset for facial similarity and introduce the Lookalike network, directed towards similar face classification, which outperforms the ad hoc usage of a face recognition network directed at the same task.

关键词： Face Face recognition Task analysis Training Feature extraction computer vision Neural networks

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Bean Split Ratio for Dry Bean Canning Quality and Variety Analysis

Bean Split Ratio for Dry Bean Canning Quality and Variety An...

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ieee/cvf conference on computer vision and pattern recognition workshops

作者： Yunfei Long Amber Bassett Karen Cichy Addie Thompson Daniel Morris Department of Electrical and Computer Engineering Michigan State University Department of Plant Soil and Microbial Sciences Michigan State University

ISBN: (数字)9781728125060

ISBN: (纸本)9781728125077

Splits on canned beans appear in the process of preparation and canning. Researchers are studying how they are influenced by cooking environment and genotype. However, there is no existing method to automatically quantify or to characterize the severity of splits. To solve this, we propose two measures: the Bean Split Ratio (BSR) that quantifies the overall severity of splits, and the Bean Split Histogram (BSH) that characterizes the size distribution of splits. We create a pixel-wise segmentation method to automatically estimate these measures from images. We also present a bean dataset of recombinant inbred lines of two genotypes, use the BSR and BSH to assess canning quality, and explore heritability of these properties.

关键词： Canning quality beans borocaptate sodium Diversion Rate AUTOMATIC size distribution inbred lines Dry beans heritability

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DSC: Dense-Sparse Convolution for Vectorized Inference of Convolutional Neural Networks

DSC: Dense-Sparse Convolution for Vectorized Inference of Co...

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ieee/cvf conference on computer vision and pattern recognition workshops

作者： Alexander Frickenstein Manoj Rohit Vemparala Christian Unger Fatih Ayar Walter Stechele BMW Group Autonomous Driving Technical University Munich Electrical and Computer Engineering

ISBN: (数字)9781728125060

ISBN: (纸本)9781728125077

The efficient applications of Convolutional Neural Networks (CNNs) in automotive-rated and safety critical hardware-accelerators require an interplay of DNN design optimization, programming techniques and hardware resources. Ad-hoc pruning would result in irregular sparsity and compression, leading to in very inefficient real world applications. Therefore, the proposed methodology, called Dense-Sparse Convolution, makes use of the right balance between pruning regularity, quantization and the underlying vectorized hardware. Different word-length compute units, e.g. CPU, are used for low-latency inference of the sparse CNNs. The proposed open-source~1 CPU-kernel is enabled to scale along with the vector word-length and the number of cores.

关键词： Convolution central processing units Neural network core Differential scanning calorimetry tree surgery PROGRAMMING TECHNIQUES hardware resource Safety critical

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