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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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04/04/2022
Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection
This paper analyses the design choices of face detection architecture th...
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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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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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09/20/2021
Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-Refinement
Recent weakly-supervised semantic segmentation (WSSS) has made remarkabl...
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06/22/2021
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack
We propose a novel and effective input transformation based adversarial ...
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06/22/2021
SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
We consider a class-incremental semantic segmentation (CISS) problem. Wh...
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03/31/2021
Rainbow Memory: Continual Learning with a Memory of Diverse Samples
Continual learning is a realistic learning scenario for AI models. Preva...
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01/01/2021
More than just an auxiliary loss: Anti-spoofing Backbone Training via Adversarial Pseudo-depth Generation
In this paper, a new method of training pipeline is discussed to achieve...
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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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06/19/2020
Efficient Active Learning for Automatic Speech Recognition via Augmented Consistency Regularization
The cost of labeling transcriptions for large speech corpora becomes a b...
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06/17/2020
StatAssist GradBoost: A Study on Optimal INT8 Quantization-aware Training from Scratch
This paper studies the scratch training of quantization-aware training (...
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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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11/20/2019
SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder
Designing a lightweight and robust portrait segmentation algorithm is an...
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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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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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08/08/2019
ExtremeC3Net: Extreme Lightweight Portrait Segmentation Networks using Advanced C3-modules
Designing a lightweight and robust portrait segmentation algorithm is an...
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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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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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05/03/2018
MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis
In this paper, we introduce a new method for generating an object image ...
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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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11/27/2017
Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams
In this work, we introduce a new algorithm for analyzing a diagram, whic...
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09/05/2017
Knowledge Sharing for Reinforcement Learning: Writing a BOOK
This paper proposes a novel deep reinforcement learning (RL) method inte...
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06/30/2017
