no code implementations • 11 Mar 2024 • Yuki Tatsukawa, I-Chao Shen, Anran Qi, Yuki Koyama, Takeo Igarashi, Ariel Shamir
To solve this problem, we present FontCLIP: a model that connects the semantic understanding of a large vision-language model with typographical knowledge.
1 code implementation • 29 Nov 2023 • Toby Chong, Alina Chadwick, I-Chao Shen, Haoran Xie, Takeo Igarashi
We repeated the process for the same skin patch under three cosmetic products.
no code implementations • 10 Jun 2022 • Hao-Kang Liu, I-Chao Shen, Bing-Yu Chen
In this paper, we introduce the first framework that enables users to remove unwanted objects or retouch undesired regions in a 3D scene represented by a pre-trained NeRF without any category-specific data and training.
no code implementations • 29 Mar 2022 • I-Chao Shen, Yu Ju Chen, Oliver van Kaick, Takeo Igarashi
The key idea of our method is the use of the Monte Carlo tree search (MCTS) algorithm and differentiable rendering to separately predict sequential topological actions and geometric actions.
no code implementations • 20 Nov 2021 • I-Chao Shen, Li-Wen Su, Yu-Ting Wu, Bing-Yu Chen
The attribute codes of the manipulated 3D shape are then "backwardly mapped" to the image latent code to obtain the final manipulated image.
no code implementations • 10 Sep 2021 • Toby Chong, I-Chao Shen, Nobuyuki Umetani, Takeo Igarashi
Furthermore, we proposed to use a custom-designed measurement garment, and we captured paired images of the measurement garment and the target garments.
no code implementations • 24 Jun 2019 • Toby Chong Long Hin, I-Chao Shen, Issei Sato, Takeo Igarashi
We present a human-in-the-optimization method that allows users to directly explore and search the latent vector space of generative image modeling.
no code implementations • 4 Sep 2018 • Shu-Hsuan Hsu, I-Chao Shen, Bing-Yu Chen
In the past few years, deep reinforcement learning has been proven to solve problems which have complex states like video games or board games.