activity
20212024
most citedRegular Time-series Generation using SGM

8 citations · 11 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Spatiotemporal Skip Guidance for Enhanced Video Diffusion Sampling

Junha Hyung, Kinam Kim, Susung Hong +2

Diffusion models have emerged as a powerful tool for generating high-quality images, videos, and 3D content. While sampling guidance techniques like CFG improve quality, they reduc…

cs.CV2024

FIMP: Future Interaction Modeling for Multi-Agent Motion Prediction

Sungmin Woo, Minjung Kim, Donghyeong Kim +2

Multi-agent motion prediction is a crucial concern in autonomous driving, yet it remains a challenge owing to the ambiguous intentions of dynamic agents and their intricate interac…

cs.LG2023

MadSGM: Multivariate Anomaly Detection with Score-based Generative Models

Haksoo Lim, Sewon Park, Minjung Kim +3

The time-series anomaly detection is one of the most fundamental tasks for time-series. Unlike the time-series forecasting and classification, the time-series anomaly detection typ…

cs.CV2023

FaceCLIPNeRF: Text-driven 3D Face Manipulation using Deformable Neural Radiance Fields

Sungwon Hwang, Junha Hyung, Daejin Kim +2

As recent advances in Neural Radiance Fields (NeRF) have enabled high-fidelity 3D face reconstruction and novel view synthesis, its manipulation also became an essential task in 3D…

cs.LG20238 cited

Regular Time-series Generation using SGM

Haksoo Lim, Minjung Kim, Sewon Park +1

Score-based generative models (SGMs) are generative models that are in the spotlight these days. Time-series frequently occurs in our daily life, e.g., stock data, climate data, an…

cs.CV2022

Tackling Background Distraction in Video Object Segmentation

Suhwan Cho, Heansung Lee, Minhyeok Lee +4

Semi-supervised video object segmentation (VOS) aims to densely track certain designated objects in videos. One of the main challenges in this task is the existence of background d…