6 citations · 11 across the 7 of their papers we have counts for
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RYOPO: Bringing End-to-End Category-Level Object Pose Estimation into Real Time
Hakjin Lee, Junghoon Seo, Jaehoon Sim
Category-level object pose estimation predicts the rotation, translation, and metric size of unseen instances within known categories. Many accurate RGB-D methods rely on external…
You Only Pose Once: A Minimalist's Detection Transformer for Monocular RGB Category-level 9D Multi-Object Pose Estimation
Hakjin Lee, Junghoon Seo, Jaehoon Sim
Accurately recovering the full 9-DoF pose of unseen instances within specific categories from a single RGB image remains a core challenge for robotics and automation. Most existing…
Masked Autoregressive Model for Weather Forecasting
Doyi Kim, Minseok Seo, Hakjin Lee +1
The growing impact of global climate change amplifies the need for accurate and reliable weather forecasting. Traditional autoregressive approaches, while effective for temporal mo…
Hausdorff Distance Matching with Adaptive Query Denoising for Rotated Detection Transformer
Hakjin Lee, MinKi Song, Jamyoung Koo +1
Detection Transformers (DETR) have recently set new benchmarks in object detection. However, their performance in detecting rotated objects lags behind established oriented object…
Implicit Stacked Autoregressive Model for Video Prediction
Minseok Seo, Hakjin Lee, Doyi Kim +1
Future frame prediction has been approached through two primary methods: autoregressive and non-autoregressive. Autoregressive methods rely on the Markov assumption and can achieve…
Self-Pair: Synthesizing Changes from Single Source for Object Change Detection in Remote Sensing Imagery
Minseok Seo, Hakjin Lee, Yongjin Jeon +1
For change detection in remote sensing, constructing a training dataset for deep learning models is difficult due to the requirements of bi-temporal supervision. To overcome this i…