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Found 19 papers, 2 papers with code
Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network
To fully explore the potential of the weak labels, we propose to impose separate treatments of strong and weak annotations via a strong-weak dual-branch network, which discriminates the massive inaccurate weak supervisions from those strong ones.
Semi-Supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
Breadth First Reasoning Graph for Multi-hop Question Answering
Recently Graph Neural Network (GNN) has been used as a promising tool in multi-hop question answering task.
Leaning Compact and Representative Features for Cross-Modality Person Re-Identification
This paper pays close attention to the cross-modality visible-infrared person re-identification (VI Re-ID) task, which aims to match human samples between visible and infrared modes.
Cross-Modality Person Re-identification
Knowledge Distillation
+1
Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition
(i) To learn more robust and discriminative features, we desire to adaptively fuse the contextual features from different layers.
Integrating Pre-trained Model into Rule-based Dialogue Management
Rule-based dialogue management is still the most popular solution for industrial task-oriented dialogue systems for their interpretablility.
HpGAN: Sequence Search with Generative Adversarial Networks
Sequences play an important role in many engineering applications and systems.
A Shared-Private Representation Model with Coarse-to-Fine Extraction for Target Sentiment Analysis
However, the relation between the target extraction task and the target classification task has not been well exploited.
Pedestrian re-identification based on Tree branch network with local and global learning
Deep part-based methods in recent literature have revealed the great potential of learning local part-level representation for pedestrian image in the task of person re-identification.
The Data Analysis Pipeline for the SDSS-IV MaNGA IFU Galaxy Survey: Overview
We summarize assessments of the precision and accuracy of our measurements as a function of signal-to-noise and other salient metrics, noting that additional analysis and discussion of emission-line diagnostics are provided in our companion paper, Belfiore et al.
Astrophysics of Galaxies
Toward Characteristic-Preserving Image-based Virtual Try-On Network
Second, to alleviate boundary artifacts of warped clothes and make the results more realistic, we employ a Try-On Module that learns a composition mask to integrate the warped clothes and the rendered image to ensure smoothness.
An MM Algorithm for Split Feasibility Problems
Furthermore, we show that the Euclidean norm appearing in the proximity function of the non-linear split feasibility problem can be replaced by arbitrary Bregman divergences.
Large-Margin Softmax Loss for Convolutional Neural Networks
Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs).
Robust Elastic Net Regression
We propose a robust elastic net (REN) model for high-dimensional sparse regression and give its performance guarantees (both the statistical error bound and the optimization bound).
Jointly Learning Non-negative Projection and Dictionary with Discriminative Graph Constraints for Classification
Sparse coding with dictionary learning (DL) has shown excellent classification performance.
Efficient Face Alignment via Locality-constrained Representation for Robust Recognition
Practical face recognition has been studied in the past decades, but still remains an open challenge.
Structured Occlusion Coding for Robust Face Recognition
We propose the structured occlusion coding (SOC) to address occlusion problems.
Latent Dictionary Learning for Sparse Representation based Classification
Each dictionary atom is jointly learned with a latent vector, which associates this atom to the representation of different classes.
Collaborative Representation based Classification for Face Recognition
It is widely believed that the l1- norm sparsity constraint on coding coefficients plays a key role in the success of SRC, while its use of all training samples to collaboratively represent the query sample is rather ignored.
Regularized Robust Coding for Face Recognition
Recently the sparse representation based classification (SRC) has been proposed for robust face recognition (FR).