13 citations · 20 across the 11 of their papers we have counts for
9 papers · 1 filter
Cascaded Robust Rectification for Arbitrary Document Images
Chaoyun Wang, Quanxin Huang, I-Chao Shen +3
Document rectification in real-world scenarios poses significant challenges due to extreme variations in camera perspectives and physical distortions. Driven by the insight that co…
LayoutRectifier: An Optimization-based Post-processing for Graphic Design Layout Generation
I-Chao Shen, Ariel Shamir, Takeo Igarashi
Recent deep learning methods can generate diverse graphic design layouts efficiently. However, these methods often create layouts with flaws, such as misalignment, unwanted overlap…
MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh
Shuangkang Fang, I-Chao Shen, Yufeng Wang +6
We present MeshLLM, a novel framework that leverages large language models (LLMs) to understand and generate text-serialized 3D meshes. Our approach addresses key limitations in ex…
NeRF Is a Valuable Assistant for 3D Gaussian Splatting
Shuangkang Fang, I-Chao Shen, Takeo Igarashi +5
We introduce NeRF-GS, a novel framework that jointly optimizes Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). This framework leverages the inherent continuous spat…
Axis-Aligned Document Dewarping
Chaoyun Wang, I-Chao Shen, Takeo Igarashi +1
Document dewarping is crucial for many applications. However, existing learning-based methods rely heavily on supervised regression with annotated data without fully leveraging the…
Low-Barrier Dataset Collection with Real Human Body for Interactive Per-Garment Virtual Try-On
Zaiqiang Wu, Yechen Li, Jingyuan Liu +4
Existing image-based virtual try-on methods are often limited to the front view and lack real-time performance. While per-garment virtual try-on methods have tackled these issues b…
Real-Time Per-Garment Virtual Try-On with Temporal Consistency for Loose-Fitting Garments
Zaiqiang Wu, I-Chao Shen, Takeo Igarashi
Per-garment virtual try-on methods collect garment-specific datasets and train networks tailored to each garment to achieve superior results. However, these approaches often strugg…
GarmentImage: Raster Encoding of Garment Sewing Patterns with Diverse Topologies
Yuki Tatsukawa, Anran Qi, I-Chao Shen +1
Garment sewing patterns are the design language behind clothing, yet their current vector-based digital representations weren't built with machine learning in mind. Vector-based re…
FontCraft: Multimodal Font Design Using Interactive Bayesian Optimization
Yuki Tatsukawa, I-Chao Shen, Mustafa Doga Dogan +4
Creating new fonts requires a lot of human effort and professional typographic knowledge. Despite the rapid advancements of automatic font generation models, existing methods requi…