3 citations · 3 across the 4 of their papers we have counts for
4 papers
Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
Seongwoong Cho, Donggyun Kim, Jinwoo Lee +1
Generalizing across robot embodiments and tasks is crucial for adaptive robotic systems. Modular policy learning approaches adapt to new embodiments but are limited to specific tas…
Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the Wild
Donggyun Kim, Seongwoong Cho, Semin Kim +2
Large language models have evolved data-efficient generalists, benefiting from the universal language interface and large-scale pre-training. However, constructing a data-efficient…
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching
Donggyun Kim, Jinwoo Kim, Seongwoong Cho +2
Dense prediction tasks are a fundamental class of problems in computer vision. As supervised methods suffer from high pixel-wise labeling cost, a few-shot learning solution that ca…
Multi-Task Neural Processes
Donggyun Kim, Seongwoong Cho, Wonkwang Lee +1
Neural Processes (NPs) consider a task as a function realized from a stochastic process and flexibly adapt to unseen tasks through inference on functions. However, naive NPs can mo…