58 citations · 74 across the 4 of their papers we have counts for
5 papers
BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation
Jungbeom Lee, Jihun Yi, Chaehun Shin +1
Weakly supervised segmentation methods using bounding box annotations focus on obtaining a pixel-level mask from each box containing an object. Existing methods typically depend on…
Interpretation of NLP models through input marginalization
Siwon Kim, Jihun Yi, Eunji Kim +1
To demystify the "black box" property of deep neural networks for natural language processing (NLP), several methods have been proposed to interpret their predictions by measuring…
iCaps: An Interpretable Classifier via Disentangled Capsule Networks
Dahuin Jung, Jonghyun Lee, Jihun Yi +1
We propose an interpretable Capsule Network, iCaps, for image classification. A capsule is a group of neurons nested inside each layer, and the one in the last layer is called a cl…
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation
Jihun Yi, Sungroh Yoon
In this paper, we address the problem of image anomaly detection and segmentation. Anomaly detection involves making a binary decision as to whether an input image contains an anom…
Energy-Based Sequence GANs for Recommendation and Their Connection to Imitation Learning
Jaeyoon Yoo, Heonseok Ha, Jihun Yi +5
Recommender systems aim to find an accurate and efficient mapping from historic data of user-preferred items to a new item that is to be liked by a user. Towards this goal, energy-…