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Found 14 papers, 4 papers with code
Knowledge Graph Completion with Counterfactual Augmentation
With a carefully designed instantiation of a causal model on the knowledge graph, we generate the counterfactual relations to answer the question by regarding the representations of entity pair given relation as context, structural information of relation-aware neighborhood as treatment, and validity of the composed triplet as the outcome.
Real-Time Super-Resolution for Real-World Images on Mobile Devices
Image Super-Resolution (ISR), which aims at recovering High-Resolution (HR) images from the corresponding Low-Resolution (LR) counterparts.
The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results
The detection of thoracic abnormalities challenge is organized by the Deepwise AI Lab.
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.
A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension
In this paper, inspired by the observation that most probing tasks involve identifying matched pairs of phrases (e. g. coreference requires matching an entity and a pronoun), we propose a pairwise probe to understand BERT fine-tuning on the machine reading comprehension (MRC) task.
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
This paper reviews the NTIRE 2020 challenge on real world super-resolution.
Residual Channel Attention Generative Adversarial Network for Image Super-Resolution and Noise Reduction
In this paper, we propose a Residual Channel Attention-Generative Adversarial Network(RCA-GAN) to solve these problems.
A Label Informative Wide \& Deep Classifier for Patents and Papers
In this paper, we provide a simple and effective baseline for classifying both patents and papers to the well-established Cooperative Patent Classification (CPC).
Feature-level and Model-level Audiovisual Fusion for Emotion Recognition in the Wild
In this paper, we proposed two strategies to fuse information extracted from different modalities, i. e., audio and visual.
Identity-Free Facial Expression Recognition using conditional Generative Adversarial Network
A novel Identity-Free conditional Generative Adversarial Network (IF-GAN) was proposed for Facial Expression Recognition (FER) to explicitly reduce high inter-subject variations caused by identity-related facial attributes, e. g., age, race, and gender.
Facial Expression Recognition
Facial Expression Recognition (FER)
Probabilistic Attribute Tree in Convolutional Neural Networks for Facial Expression Recognition
In this paper, we proposed a novel Probabilistic Attribute Tree-CNN (PAT-CNN) to explicitly deal with the large intra-class variations caused by identity-related attributes, e. g., age, race, and gender.
Facial Expression Recognition
Facial Expression Recognition (FER)
Island Loss for Learning Discriminative Features in Facial Expression Recognition
Over the past few years, Convolutional Neural Networks (CNNs) have shown promise on facial expression recognition.
Ranked #3 on
Facial Expression Recognition (FER)
on SFEW
Facial Expression Recognition
Facial Expression Recognition (FER)
Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition
Most recently, Convolutional Neural Networks (CNNs) have shown promise for facial AU recognition, where predefined and fixed convolution filter sizes are employed.
