AIMC Journal:
IEEE transactions on pattern analysis and machine intelligence

Showing 221 to 230 of 300 articles

Semantic Face Hallucination: Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes.

IEEE transactions on pattern analysis and machine intelligence May 14, 2019
Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolution (HR) counterpart by learning a mapping from an exemplary dataset. Since a low-resolution (LR) input patch may correspond to many HR candidate patc...
Face Image Processing, Computer-Assisted Semantics Machine Learning Algorithms Humans Neural Networks, Computer
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NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding.

IEEE transactions on pattern analysis and machine intelligence May 14, 2019
Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-based and RGB+D-based action recognition benchmarks have a number of l...
Semantics Pattern Recognition, Automated Benchmarking Video Recording Human Activities Humans Deep Learning Image Processing, Computer-Assisted Algorithms
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[Formula: see text]-Patches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors.

IEEE transactions on pattern analysis and machine intelligence May 10, 2019
In this paper, a novel benchmark is introduced for evaluating local image descriptors. We demonstrate limitations of the commonly used datasets and evaluation protocols, that lead to ambiguities and contradictory results in the literature. Furthermor...
Deep Learning Image Processing, Computer-Assisted Algorithms
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Face Hallucination by Attentive Sequence Optimization with Reinforcement Learning.

IEEE transactions on pattern analysis and machine intelligence May 7, 2019
Face hallucination is a domain-specific super-resolution problem that aims to generate a high-resolution (HR) face image from a low-resolution (LR) input. In contrast to the existing patch-wise super-resolution models that divide a face image into re...
Humans Face Algorithms Neural Networks, Computer Image Processing, Computer-Assisted Machine Learning
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Defining Image Memorability Using the Visual Memory Schema.

IEEE transactions on pattern analysis and machine intelligence May 2, 2019
Memorability of an image is a characteristic determined by the human observers' ability to remember images they have seen. Yet recent work on image memorability defines it as an intrinsic property that can be obtained independent of the observer. The...
Adult Middle Aged Deep Learning Aged, 80 and over Young Adult Memory Visual Perception Fixation, Ocular Image Processing, Computer-Assisted Humans Algorithms Artificial Intelligence Models, Neurological Aged
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Significance of Softmax-Based Features in Comparison to Distance Metric Learning-Based Features.

IEEE transactions on pattern analysis and machine intelligence Apr 15, 2019
End-to-end distance metric learning (DML) has been applied to obtain features useful in many computer vision tasks. However, these DML studies have not provided equitable comparisons between features extracted from DML-based networks and softmax-base...
Neural Networks, Computer Image Processing, Computer-Assisted Cluster Analysis Automobiles Birds Databases, Factual Animals Deep Learning
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Synthesizing Supervision for Learning Deep Saliency Network without Human Annotation.

IEEE transactions on pattern analysis and machine intelligence Feb 20, 2019
Recently, the research field of salient object detection is undergoing a rapid and remarkable development along with the wide usage of deep neural networks. Being trained with a large number of images annotated with strong pixel-level ground-truth ma...
Humans Image Processing, Computer-Assisted Animals Supervised Machine Learning Algorithms Deep Learning Video Recording
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End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning.

IEEE transactions on pattern analysis and machine intelligence Feb 14, 2019
We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera control signals as output (e.g., move forward, turn left, etc.). Conventional methods tackle tracking an...
Databases, Factual Deep Learning Video Recording Image Processing, Computer-Assisted Machine Learning Algorithms Humans Neural Networks, Computer
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Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation.

IEEE transactions on pattern analysis and machine intelligence Jan 22, 2019
We investigate two crucial and closely-related aspects of CNNs for optical flow estimation: models and training. First, we design a compact but effective CNN model, called PWC-Net, according to simple and well-established principles: pyramidal proces...
Databases, Factual Neural Networks, Computer Image Processing, Computer-Assisted Software Humans
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Feature Boosting Network For 3D Pose Estimation.

IEEE transactions on pattern analysis and machine intelligence Jan 22, 2019
In this paper, a feature boosting network is proposed for estimating 3D hand pose and 3D body pose from a single RGB image. In this method, the features learned by the convolutional layers are boosted with a new long short-term dependence-aware (LSTD...
Posture Reproducibility of Results Hand Humans Imaging, Three-Dimensional Machine Learning
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