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DVC-Net: a new dual-view context-aware network for emotion recognition in the wild
Emotion recognition in the wild (ERW) is a challenging task due to unknown and the unconstrained scenes in the wild environment. Different from...
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Deep feature voting: a semantic-driven and local context-aware approach for image classification
In the context of addressing new image classification tasks with insufficient training samples via pre-trained deep learning models, the methods...
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Context-Aware Enhanced Virtual Try-On Network with fabric adaptive registration
Image-based virtual try-on technology provides a better shop** experience for online customers and holds immense commercial value. However,...
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Dual-Stream Context-Aware Neural Network for Survival Prediction from Whole Slide Images
Whole slide images (WSI) encompass a wealth of information about the tumor micro-environment, which holds prognostic value for patients’ survival....
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Evaluating Word Embedding Feature Extraction Techniques for Host-Based Intrusion Detection Systems
Research into Intrusion and Anomaly Detectors at the Host level typically pays much attention to extracting attributes from system call traces. These...
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A Context Aware Lung Cancer Survival Prediction Network by Using Whole Slide Images
Lung cancer has caused enormous harm to human life and traditional whole slide image (WSI) based lung cancer survival prediction methods suffer from...
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Stacked cross-modal feature consolidation attention networks for image captioning
The attention-enriched encoder-decoder framework has recently aroused great interest in image captioning due to its overwhelming progress. Many...
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A Dynamic Feature Interaction Framework for Multi-task Visual Perception
Multi-task visual perception has a wide range of applications in scene understanding such as autonomous driving. In this work, we devise an efficient...
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Visualizations for universal deep-feature representations: survey and taxonomy
In data science and content-based retrieval, we find many domain-specific techniques that employ a data processing pipeline with two fundamental...
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ADOSMNet: a novel visual affordance detection network with object shape mask guided feature encoders
Visual affordance detection aims to understand the functional attributes of objects, which is crucial for robots to achieve interactive tasks. Most...
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EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection
Good proposal initials are critical for 3D object detection applications. However, due to the significant geometry variation of indoor scenes,...
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Multimodal emotion recognition model via hybrid model with improved feature level fusion on facial and EEG feature set
In recent years, academics have placed a high value on multi-modal emotion identification, as well as extensive research has been conducted in the...
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Enhanced feature pyramid for multi-view stereo with adaptive correlation cost volume
AbstractMulti-level features are commonly employed in the cascade network, which is currently the dominant framework in multi-view stereo (MVS)....
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Deep neural networks for explainable feature extraction in orchid identification
Automated image-based plant identification systems are black-boxes, failing to provide an explanation of a classification. Such explanations are seen...
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Customizing the feature modulation for visual tracking
In visual tracking, the target always undergoes appearance variations due to a variety of challenging situations, such as deformation and rotation....
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Training a Multi-task Model for Classification and Grasp Detection of Surgical Tools Using Transfer Learning
This paper proposes a multi-task model for the classification and grasp detection of surgical tools so that the tasks such as handing, collection...
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Region Feature Disentanglement for Domain Adaptive Object Detection
In recent years, deep learning based object detection has shown impressive results. However, applying an object detector learned from one data domain...
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Few-shot defect detection using feature enhancement and image generation for manufacturing quality inspection
Visual defect detection, which is pivotal in industrial quality control, often requires extensive datasets for training deep-learning models....
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An efficient multi-scale contextual feature fusion network for counting crowds with varying densities and scales
The crowd counting problem aims to predict the number of pedestrians in a surveillance video or an image and produce a crowd density map. Achieving...
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Less Is More: Similarity Models for Content-Based Video Retrieval
The concept of object-to-object similarity plays a crucial role in interactive content-based video retrieval tools. Similarity (or distance) models...