Deep Attention
37 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Deep Attention
Google Refexp
METU-VIREF Dataset
Most implemented papers
RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans
Automatic extraction of liver and tumor from CT volumes is a challenging task due to their heterogeneous and diffusive shapes.
Multi-scale self-guided attention for medical image segmentation
sinAshish/Multi-Scale-Attention
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arXiv preprint 2019
In this paper we attempt to overcome these limitations with the proposed architecture, by capturing richer contextual dependencies based on the use of guided self-attention mechanisms.
Dan: Deep attention neural network for news recommendation
With the rapid information explosion of news, making personalized news recommendation for users becomes an increasingly challenging problem.
Compact Global Descriptor for Neural Networks
HolmesShuan/Compact-Global-Descriptor
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Long-range dependencies modeling, widely used in capturing spatiotemporal correlation, has shown to be effective in CNN dominated computer vision tasks.
Searching for Ambiguous Objects in Videos using Relational Referring Expressions
Especially in ambiguous settings, humans prefer expressions (called relational referring expressions) that describe an object with respect to a distinguishing, unique object.
PDANet: Polarity-consistent Deep Attention Network for Fine-grained Visual Emotion Regression
ZizhouJia/PDANet
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By optimizing the PCR loss, PDANet can generate a polarity preserved attention map and thus improve the emotion regression performance.
Deep attention networks reveal the rules of collective motion in zebrafish
When using simulated trajectories, the model recovers the ground-truth interaction rule used to generate them, as well as the number of interacting neighbours.
Deep Attention Based Semi-Supervised 2D-Pose Estimation for Surgical Instruments
To this end, a lightweight network architecture is introduced and mean teacher, virtual adversarial training and pseudo-labeling algorithms are evaluated on 2D-pose estimation for surgical instruments.
Detecting Attended Visual Targets in Video
ejcgt/attention-target-detection
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CVPR 2020
We address the problem of detecting attention targets in video.
Image Search With Text Feedback by Visiolinguistic Attention Learning
yanbeic/VAL
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CVPR 2020
In this work, we tackle this task by a novel Visiolinguistic Attention Learning (VAL) framework.
