93 citations · 97 across the 10 of their papers we have counts for
10 papers
When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series
Min-Yeong Park, Won-Jeong Lee, Seong Tae Kim +1
Recently, forecasting future abnormal events has emerged as an important scenario to tackle real-world necessities. However, the solution of predicting specific future time points…
ESC: Erasing Space Concept for Knowledge Deletion
Tae-Young Lee, Sundong Park, Minwoo Jeon +2
As concerns regarding privacy in deep learning continue to grow, individuals are increasingly apprehensive about the potential exploitation of their personal knowledge in trained m…
Towards High-fidelity Head Blending with Chroma Keying for Industrial Applications
Hah Min Lew, Sahng-Min Yoo, Hyunwoo Kang +1
We introduce an industrial Head Blending pipeline for the task of seamlessly integrating an actor's head onto a target body in digital content creation. The key challenge stems fro…
Online Continuous Generalized Category Discovery
Keon-Hee Park, Hakyung Lee, Kyungwoo Song +1
With the advancement of deep neural networks in computer vision, artificial intelligence (AI) is widely employed in real-world applications. However, AI still faces limitations in…
Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners
Keon-Hee Park, Kyungwoo Song, Gyeong-Moon Park
Few-Shot Class Incremental Learning (FSCIL) is a task that requires a model to learn new classes incrementally without forgetting when only a few samples for each class are given.…
LFS-GAN: Lifelong Few-Shot Image Generation
Juwon Seo, Ji-Su Kang, Gyeong-Moon Park
We address a challenging lifelong few-shot image generation task for the first time. In this situation, a generative model learns a sequence of tasks using only a few samples per t…