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20212026
most citedMetropolis-Hastings Data Augmentation for Graph Neural Networks

7 citations · 13 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Learning to Solve Generative ODEs Beyond the Linear Span

Sihyeon Kim, Seunghun Lee, Vikas Singh +1

Diffusion and flow generative models sample by integrating a learned ODE, but high quality still requires many sequential model evaluations. Solver learning reduces this cost by ad…

cs.CV2025

ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models

Dohwan Ko, Sihyeon Kim, Yumin Suh +4

Spatio-temporal reasoning is essential in understanding real-world environments in various fields, eg, autonomous driving and sports analytics. Recent advances have improved the sp…

cs.CV2023

Semantic-Aware Implicit Template Learning via Part Deformation Consistency

Sihyeon Kim, Minseok Joo, Jaewon Lee +3

Learning implicit templates as neural fields has recently shown impressive performance in unsupervised shape correspondence. Despite the success, we observe current approaches, whi…

cs.CV2023★ 5 cited

Self-positioning Point-based Transformer for Point Cloud Understanding

Jinyoung Park, Sanghyeok Lee, Sihyeon Kim +2

Transformers have shown superior performance on various computer vision tasks with their capabilities to capture long-range dependencies. Despite the success, it is challenging to…

cs.CV2021★ 1 cited

Point Cloud Augmentation with Weighted Local Transformations

Sihyeon Kim, Sanghyeok Lee, Dasol Hwang +3

Despite the extensive usage of point clouds in 3D vision, relatively limited data are available for training deep neural networks. Although data augmentation is a standard approach…