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06/20/2023
Augmenting Sub-model to Improve Main Model
Image classification has improved with the development of training techn...
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05/15/2023
GeNAS: Neural Architecture Search with Better Generalization
Neural Architecture Search (NAS) aims to automatically excavate the opti...
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03/30/2023
Neglected Free Lunch – Learning Image Classifiers Using Annotation Byproducts
Supervised learning of image classifiers distills human knowledge into a...
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03/27/2023
The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation
In this paper, we introduce a novel learning scheme named weakly semi-su...
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10/20/2022
Similarity of Neural Architectures Based on Input Gradient Transferability
In this paper, we aim to design a quantitative similarity function betwe...
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10/16/2022
Scratching Visual Transformer's Back with Uniform Attention
The favorable performance of Vision Transformers (ViTs) is often attribu...
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07/19/2022
Time Is MattEr: Temporal Self-supervision for Video Transformers
Understanding temporal dynamics of video is an essential aspect of learn...
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04/25/2022
Loss-based Sequential Learning for Active Domain Adaptation
Active domain adaptation (ADA) studies have mainly addressed query selec...
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04/08/2022
Spatiotemporal Augmentation on Selective Frequencies for Video Representation Learning
Recent self-supervised video representation learning methods focus on ma...
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03/28/2022
Demystifying the Neural Tangent Kernel from a Practical Perspective: Can it be trusted for Neural Architecture Search without training?
In Neural Architecture Search (NAS), reducing the cost of architecture e...
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02/06/2022
Learning Features with Parameter-Free Layers
Trainable layers such as convolutional building blocks are the standard ...
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11/30/2021
Donut: Document Understanding Transformer without OCR
Understanding document images (e.g., invoices) has been an important res...
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11/26/2021
Contrastive Vicinal Space for Unsupervised Domain Adaptation
Utilizing vicinal space between the source and target domains is one of ...
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03/30/2021
Rethinking Spatial Dimensions of Vision Transformers
Vision Transformer (ViT) extends the application range of transformers f...
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01/13/2021
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels
ImageNet has been arguably the most popular image classification benchma...
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12/07/2020
VideoMix: Rethinking Data Augmentation for Video Classification
State-of-the-art video action classifiers often suffer from overfitting....
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07/02/2020
ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network
This paper addresses representational bottleneck in a network and propos...
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06/15/2020
Slowing Down the Weight Norm Increase in Momentum-based Optimizers
Normalization techniques, such as batch normalization (BN), have led to ...
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03/09/2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods
Despite apparent human-level performances of deep neural networks (DNN),...
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06/15/2019
EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
In this paper, we propose a new multi-scale face detector having an extr...
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05/13/2019
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Regional dropout strategies have been proposed to enhance the performanc...
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04/03/2019
Character Region Awareness for Text Detection
Scene text detection methods based on neural networks have emerged recen...
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04/03/2019
What is wrong with scene text recognition model comparisons? dataset and model analysis
Many new proposals for scene text recognition (STR) models have been int...
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12/12/2018
Concentrated-Comprehensive Convolutions for lightweight semantic segmentation
The semantic segmentation requires a lot of computational cost. The dila...
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10/10/2016
