1 citations · 1 across the 4 of their papers we have counts for
5 papers
HimmBO: High-Dimensional Interactive Model-Merging Bayesian Optimization for Image Generation
Jinyuan Mao, Zhihao Shen, Chenxi Liu
Fine-tuning has become a common way to customize text-to-image models, leading to community collections of over 100K lightweight adapters. Adapters sharing a base model can be merg…
SemLayer: Semantic-aware Generative Segmentation and Layer Construction for Abstract Icons
Haiyang Xu, Ronghuan Wu, Li-Yi Wei +5
Graphic icons are a cornerstone of modern design workflows, yet they are often distributed as flattened single-path or compound-path graphics, where the original semantic layering…
GimmBO: Interactive Generative Image Model Merging via Bayesian Optimization
Chenxi Liu, Selena Ling, Alec Jacobson
Fine-tuning-based adaptation is widely used to customize diffusion-based image generation, leading to large collections of community-created adapters that capture diverse subjects…
Mesh Processing Non-Meshes via Neural Displacement Fields
Yuta Noma, Zhecheng Wang, Chenxi Liu +2
Mesh processing pipelines are mature, but adapting them to newer non-mesh surface representations -- which enable fast rendering with compact file size -- requires costly meshing o…
A LoRA is Worth a Thousand Pictures
Chenxi Liu, Towaki Takikawa, Alec Jacobson
Low-Rank Adaptation (LoRA) has become a standard approach for parameter-efficient fine-tuning of image diffusion models, with over 200K models trained to replicate artistic styles…