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07/04/2023
ProPILE: Probing Privacy Leakage in Large Language Models
The rapid advancement and widespread use of large language models (LLMs)...
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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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05/27/2023
MPCHAT: Towards Multimodal Persona-Grounded Conversation
In order to build self-consistent personalized dialogue agents, previous...
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05/24/2023
Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models
Advances in Large Language Models (LLMs) have inspired a surge of resear...
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05/24/2023
Who Wrote this Code? Watermarking for Code Generation
Large language models for code have recently shown remarkable performanc...
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04/21/2023
RoCOCO: Robust Benchmark MS-COCO to Stress-test Robustness of Image-Text Matching Models
Recently, large-scale vision-language pre-training models and visual sem...
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04/10/2023
Three Recipes for Better 3D Pseudo-GTs of 3D Human Mesh Estimation in the Wild
Recovering 3D human mesh in the wild is greatly challenging as in-the-wi...
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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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03/21/2023
CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion
This paper proposes a novel diffusion-based model, CompoDiff, for solvin...
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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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01/29/2023
Neural Relation Graph for Identifying Problematic Data
Diagnosing and cleaning datasets are crucial for building robust machine...
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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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08/21/2022
A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective
We propose the first unified theoretical analysis of mixed sample data a...
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06/30/2022
Exploring Temporally Dynamic Data Augmentation for Video Recognition
Data augmentation has recently emerged as an essential component of mode...
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05/30/2022
Dataset Condensation via Efficient Synthetic-Data Parameterization
The great success of machine learning with massive amounts of data comes...
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03/08/2022
Weakly Supervised Semantic Segmentation using Out-of-Distribution Data
Weakly supervised semantic segmentation (WSSS) methods are often built o...
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02/07/2022
Dataset Condensation with Contrastive Signals
Recent studies have demonstrated that gradient matching-based dataset sy...
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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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11/30/2021
Donut: Document Understanding Transformer without OCR
Understanding document images (e.g., invoices) has been an important res...
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10/08/2021
Observations on K-image Expansion of Image-Mixing Augmentation for Classification
Image-mixing augmentations (e.g., Mixup or CutMix), which typically mix ...
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10/06/2021
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective
Deep neural networks (DNNs) often rely on easy-to-learn discriminatory f...
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10/03/2021
Progressive Transmission and Inference of Deep Learning Models
Modern image files are usually progressively transmitted and provide a p...
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07/28/2021
Normalization Matters in Weakly Supervised Object Localization
Weakly-supervised object localization (WSOL) enables finding an object u...
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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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10/15/2019
Neural Approximation of an Auto-Regressive Process through Confidence Guided Sampling
We propose a generic confidence-based approximation that can be plugged ...
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10/07/2019
Learning De-biased Representations with Biased Representations
Many machine learning algorithms are trained and evaluated by splitting ...
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08/12/2019
Variational Autoencoded Regression: High Dimensional Regression of Visual Data on Complex Manifold
This paper proposes a new high dimensional regression method by merging ...
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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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04/03/2019
A Comprehensive Overhaul of Feature Distillation
We investigate the design aspects of feature distillation methods achiev...
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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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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
Improving Knowledge Distillation with Supporting Adversarial Samples
Many recent works on knowledge distillation have provided ways to transf...
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03/28/2018
Context-aware Deep Feature Compression for High-speed Visual Tracking
We propose a new context-aware correlation filter based tracking framewo...
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11/27/2017
Butterfly Effect: Bidirectional Control of Classification Performance by Small Additive Perturbation
This paper proposes a new algorithm for controlling classification resul...
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03/31/2017