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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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03/20/2023
SeiT: Storage-Efficient Vision Training with Tokens Using 1 Storage
We need billion-scale images to achieve more generalizable and ground-br...
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12/08/2022
Group Generalized Mean Pooling for Vision Transformer
Vision Transformer (ViT) extracts the final representation from either c...
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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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06/30/2022
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation
Ensembles of deep neural networks have demonstrated superior performance...
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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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12/01/2021
The Majority Can Help The Minority: Context-rich Minority Oversampling for Long-tailed Classification
The problem of class imbalanced data lies in that the generalization per...
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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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02/05/2021
Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching
Knowledge distillation extracts general knowledge from a pre-trained tea...
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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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04/03/2019
A Comprehensive Overhaul of Feature Distillation
We investigate the design aspects of feature distillation methods achiev...
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01/18/2019
Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification
In person re-identification (ReID) task, because of its shortage of trai...
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11/08/2018
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons
An activation boundary for a neuron refers to a separating hyperplane th...
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05/15/2018
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary
Many recent works on knowledge distillation have provided ways to transf...
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05/15/2018
