Deep Learning based Food Instance Segmentation using Synthetic Data. - Deokhwan Park; Joosoon Lee; Junseok Lee 003; Kyoobin Lee (UR, 2021)

Object Detection for Understanding Assembly Instruction Using Context-aware Data Augmentation and Cascade Mask R-CNN. - Joosoon Lee; Seongju Lee; Seunghyeok Back; Sungho Shin; Kyoobin Lee (CoRR, 2021)

Teaching Where to Look: Attention Similarity Knowledge Distillation for Low Resolution Face Recognition. - Sungho Shin; Joosoon Lee; Junseok Lee 003; Yeonguk Yu; Kyoobin Lee (ECCV (12), 2022)

Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling. - Seunghyeok Back; Joosoon Lee; Taewon Kim; Sangjun Noh; Raeyoung Kang; Seongho Bak; Kyoobin Lee (ICRA, 2022)

INSTA-BEEER: Explicit Error Estimation and Refinement for Fast and Accurate Unseen Object Instance Segmentation. - Seunghyeok Back; Sangbeom Lee; Kangmin Kim; Joosoon Lee; Sungho Shin; Jaemo Maeng; Kyoobin Lee (CoRR, 2023)

PolyFit: A Peg-in-hole Assembly Framework for Unseen Polygon Shapes via Sim-to-real Adaptation. - Geonhyup Lee; Joosoon Lee; Sangjun Noh; Minhwan Ko; Kangmin Kim; Kyoobin Lee (IROS, 2024)

Seq2Act: A Sequence-to-Action Framework for Novel Shapes in Robotic Peg-in-Hole Assembly. - Geonhyup Lee; Joosoon Lee; Kyoobin Lee (UR, 2024)

PDCC: Peg-in-Hole Framework via Dynamic Continuous Contact Data. - Joosoon Lee; Geonhyup Lee; Kyoobin Lee (UR, 2024)

GraspClutter6D: A Large-scale Real-world Dataset for Robust Perception and Grasping in Cluttered Scenes. - Seunghyeok Back; Joosoon Lee; Kangmin Kim; Heeseon Rho; Geonhyup Lee; Raeyoung Kang; Sangbeom Lee; Sangjun Noh; Youngjin Lee; Taeyeop Lee; Kyoobin Lee (CoRR, 2025)