activity
20182025
most citedClipGen: A Deep Generative Model for Clipart Vectorization and Synthesis

29 citations · 45 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2025

AutoSketch: VLM-assisted Style-Aware Vector Sketch Completion

Hsiao-Yuan Chin, I-Chao Shen, Yi-Ting Chiu +2

The ability to automatically complete a partial sketch that depicts a complex scene, e.g., "a woman chatting with a man in the park", is very useful. However, existing sketch gener…

cs.GR2023★ 1 cited

EvIcon: Designing High-Usability Icon with Human-in-the-loop Exploration and IconCLIP

I-Chao Shen, Fu-Yin Cherng, Takeo Igarashi +2

Interface icons are prevalent in various digital applications. Due to limited time and budgets, many designers rely on informal evaluation, which often results in poor usability ic…

cs.CV2022★ 15 cited

NeRF-In: Free-Form NeRF Inpainting with RGB-D Priors

Hao-Kang Liu, I-Chao Shen, Bing-Yu Chen

Though Neural Radiance Field (NeRF) demonstrates compelling novel view synthesis results, it is still unintuitive to edit a pre-trained NeRF because the neural network's parameters…

cs.CV2022

AutoPoly: Predicting a Polygonal Mesh Construction Sequence from a Silhouette Image

I-Chao Shen, Yu Ju Chen, Oliver van Kaick +1

Polygonal modeling is a core task of content creation in Computer Graphics. The complexity of modeling, in terms of the number and the order of operations and time required to exec…

cs.CV2021

StylePart: Image-based Shape Part Manipulation

I-Chao Shen, Li-Wen Su, Yu-Ting Wu +1

Due to a lack of image-based "part controllers", shape manipulation of man-made shape images, such as resizing the backrest of a chair or replacing a cup handle is not intuitive. T…

cs.GR2021

Per Garment Capture and Synthesis for Real-time Virtual Try-on

Toby Chong, I-Chao Shen, Nobuyuki Umetani +1

Virtual try-on is a promising application of computer graphics and human computer interaction that can have a profound real-world impact especially during this pandemic. Existing i…

cs.GR2021★ 29 cited

ClipGen: A Deep Generative Model for Clipart Vectorization and Synthesis

I-Chao Shen, Bing-Yu Chen

This paper presents a novel deep learning-based approach for automatically vectorizing and synthesizing the clipart of man-made objects. Given a raster clipart image and its corres…

cs.GR2020

ClipFlip : Multi-view Clipart Design

I-Chao Shen, Kuan-Hung Liu, Li-Wen Su +2

We present an assistive system for clipart design by providing visual scaffolds from the unseen viewpoints. Inspired by the artists' creation process, our system constructs the vis…

cs.GR2019

ZomeFab: Cost-effective Hybrid Fabrication with Zometools

I-Chao Shen, Ming-Shiuan Chen, Chun-Kai Huang +1

In recent years, personalized fabrication has received considerable attention because of the widespread use of consumer-level three-dimensional (3D) printers. However, such 3D prin…

cs.GR2019

Interactive Optimization of Generative Image Modeling using Sequential Subspace Search and Content-based Guidance

Toby Chong Long Hin, I-Chao Shen, Issei Sato +1

Generative image modeling techniques such as GAN demonstrate highly convincing image generation result. However, user interaction is often necessary to obtain the desired results.…

cs.GR2018

Texturing and Deforming Meshes with Casual Images

I-Chao Shen, Yi-Hau Wang, Yu-Mei Chen +1

Using (casual) images to texture 3D models is a common way to create realistic 3D models, which is a very important task in computer graphics. However, if the shape of the casual i…

cs.LG2018

Transferring Deep Reinforcement Learning with Adversarial Objective and Augmentation

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. The next step of intelligent agents…