613 citations · 849 across the 26 of their papers we have counts for
26 papers
Topic-VQ-VAE: Leveraging Latent Codebooks for Flexible Topic-Guided Document Generation
YoungJoon Yoo, Jongwon Choi
This paper introduces a novel approach for topic modeling utilizing latent codebooks from Vector-Quantized Variational Auto-Encoder~(VQ-VAE), discretely encapsulating the rich info…
Gaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video Grounding
Sunoh Kim, Jungchan Cho, Joonsang Yu +2
In the weakly supervised temporal video grounding study, previous methods use predetermined single Gaussian proposals which lack the ability to express diverse events described by…
GeNAS: Neural Architecture Search with Better Generalization
Joonhyun Jeong, Joonsang Yu, Geondo Park +2
Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches…
EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection
Joonhyun Jeong, Beomyoung Kim, Joonsang Yu +1
This paper analyzes the design choices of face detection architecture that improve efficiency of computation cost and accuracy. Specifically, we re-examine the effectiveness of the…
Learning Features with Parameter-Free Layers
Dongyoon Han, YoungJoon Yoo, Beomyoung Kim +1
Trainable layers such as convolutional building blocks are the standard network design choices by learning parameters to capture the global context through successive spatial opera…
Observations on K-image Expansion of Image-Mixing Augmentation for Classification
Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo +3
Image-mixing augmentations (e.g., Mixup and CutMix), which typically involve mixing two images, have become the de-facto training techniques for image classification. Despite their…