1 citations · 2 across the 4 of their papers we have counts for
5 papers · 1 filter
Interactive Multi-Head Self-Attention with Linear Complexity
Hankyul Kang, Ming-Hsuan Yang, Jongbin Ryu
We propose an efficient interactive method for multi-head self-attention via decomposition. For existing methods using multi-head self-attention, the attention operation of each he…
Gramian Attention Heads are Strong yet Efficient Vision Learners
Jongbin Ryu, Dongyoon Han, Jongwoo Lim
We introduce a novel architecture design that enhances expressiveness by incorporating multiple head classifiers (\ie, classification heads) instead of relying on channel expansion…
Fine-Grained Self-Supervised Learning with Jigsaw Puzzles for Medical Image Classification
Wongi Park, Jongbin Ryu
Classifying fine-grained lesions is challenging due to minor and subtle differences in medical images. This is because learning features of fine-grained lesions with highly minor d…
Robust Asymmetric Loss for Multi-Label Long-Tailed Learning
Wongi Park, Inhyuk Park, Sungeun Kim +1
In real medical data, training samples typically show long-tailed distributions with multiple labels. Class distribution of the medical data has a long-tailed shape, in which the i…
Spatial Bias for Attention-free Non-local Neural Networks
Junhyung Go, Jongbin Ryu
In this paper, we introduce the spatial bias to learn global knowledge without self-attention in convolutional neural networks. Owing to the limited receptive field, conventional c…