no code implementations • 7 Nov 2023 • Hyunwoo Lee, Yunho Kim, Seung Yeop Yang, Hayoung Choi
The problem of \textquotedblleft dying ReLU," where ReLU neurons become inactive and yield zero output, presents a significant challenge in the training of deep neural networks with ReLU activation function.
no code implementations • 24 Aug 2023 • Yunho Kim, Hyunsik Oh, Jeonghyun Lee, Jinhyeok Choi, Gwanghyeon Ji, Moonkyu Jung, Donghoon Youm, Jemin Hwangbo
In this work, we propose a novel reinforcement learning framework for training neural network controllers for complex robotic systems consisting of both rewards and constraints.
1 code implementation • 27 Dec 2022 • Kihong Kim, Yunho Kim, Seokju Cho, Junyoung Seo, Jisu Nam, Kychul Lee, Seungryong Kim, Kwanghee Lee
In this paper, we propose a diffusion-based face swapping framework for the first time, called DiffFace, composed of training ID conditional DDPM, sampling with facial guidance, and a target-preserving blending.
1 code implementation • 19 Apr 2022 • Yunho Kim, Chanyoung Kim, Jemin Hwangbo
For autonomous quadruped robot navigation in various complex environments, a typical SOTA system is composed of four main modules -- mapper, global planner, local planner, and command-tracking controller -- in a hierarchical manner.
1 code implementation • 9 Dec 2021 • Yunho Kim, Bukun Son, Dongjun Lee
There is a growing interest in learning a velocity command tracking controller of quadruped robot using reinforcement learning due to its robustness and scalability.
Hierarchical Reinforcement Learning reinforcement-learning +1