activity
20192022
most citedPin the Memory: Learning to Generalize Semantic Segmentation

6 citations · 15 across the 6 of their papers we have counts for

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9 papers · 1 filter

cs.CV2022

SimOn: A Simple Framework for Online Temporal Action Localization

Tuan N. Tang, Jungin Park, Kwonyoung Kim +1

Online Temporal Action Localization (On-TAL) aims to immediately provide action instances from untrimmed streaming videos. The model is not allowed to utilize future frames and any…

cs.CV2022

Language-free Training for Zero-shot Video Grounding

Dahye Kim, Jungin Park, Jiyoung Lee +2

Given an untrimmed video and a language query depicting a specific temporal moment in the video, video grounding aims to localize the time interval by understanding the text and vi…

cs.CV20226 cited

Pin the Memory: Learning to Generalize Semantic Segmentation

Jin Kim, Jiyoung Lee, Jungin Park +2

The rise of deep neural networks has led to several breakthroughs for semantic segmentation. In spite of this, a model trained on source domain often fails to work properly in new…

cs.CV20225 cited

Probabilistic Representations for Video Contrastive Learning

Jungin Park, Jiyoung Lee, Ig-Jae Kim +1

This paper presents Probabilistic Video Contrastive Learning, a self-supervised representation learning method that bridges contrastive learning with probabilistic representation.…

cs.CV20213 cited

Self-balanced Learning For Domain Generalization

Jin Kim, Jiyoung Lee, Jungin Park +2

Domain generalization aims to learn a prediction model on multi-domain source data such that the model can generalize to a target domain with unknown statistics. Most existing appr…

cs.CV2021

Bridge to Answer: Structure-aware Graph Interaction Network for Video Question Answering

Jungin Park, Jiyoung Lee, Kwanghoon Sohn

This paper presents a novel method, termed Bridge to Answer, to infer correct answers for questions about a given video by leveraging adequate graph interactions of heterogeneous c…