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20152022
most citedUnsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks

30 citations · 43 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV20225 cited

ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization

Jiwon Kim, Youngjo Min, Daehwan Kim +4

We present a novel semi-supervised learning framework that intelligently leverages the consistency regularization between the model's predictions from two strongly-augmented views…

cs.CV2022

Joint Learning of Feature Extraction and Cost Aggregation for Semantic Correspondence

Jiwon Kim, Youngjo Min, Mira Kim +1

Establishing dense correspondences across semantically similar images is one of the challenging tasks due to the significant intra-class variations and background clutters. To solv…

cs.CV20221 cited

Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels

Jiwon Kim, Kwangrok Ryoo, Junyoung Seo +4

Establishing dense correspondences across semantically similar images remains a challenging task due to the significant intra-class variations and background clutters. Traditionall…

cs.CV201730 cited

Unsupervised Visual Attribute Transfer with Reconfigurable Generative Adversarial Networks

Taeksoo Kim, Byoungjip Kim, Moonsu Cha +1

Learning to transfer visual attributes requires supervision dataset. Corresponding images with varying attribute values with the same identity are required for learning the transfe…

cs.CV2017

End-to-end Learning of Image based Lane-Change Decision

Seong-Gyun Jeong, Jiwon Kim, Sujung Kim +1

We propose an image based end-to-end learning framework that helps lane-change decisions for human drivers and autonomous vehicles. The proposed system, Safe Lane-Change Aid Networ…