24 citations · 43 across the 23 of their papers we have counts for
9 papers · 1 filter
Split-and-Fit: Learning B-Reps via Structure-Aware Voronoi Partitioning
Yilin Liu, Jiale Chen, Shanshan Pan +3
We introduce a novel method for acquiring boundary representations (B-Reps) of 3D CAD models which involves a two-step process: it first applies a spatial partitioning, referred to…
Layered Image Vectorization via Semantic Simplification
Zhenyu Wang, Jianxi Huang, Zhida Sun +3
This work presents a progressive image vectorization technique that reconstructs the raster image as layer-wise vectors from semantic-aligned macro structures to finer details. Our…
EmoEdit: Evoking Emotions through Image Manipulation
Jingyuan Yang, Jiawei Feng, Weibin Luo +3
Affective Image Manipulation (AIM) seeks to modify user-provided images to evoke specific emotional responses. This task is inherently complex due to its twofold objective: signifi…
MyVLM: Personalizing VLMs for User-Specific Queries
Yuval Alaluf, Elad Richardson, Sergey Tulyakov +2
Recent large-scale vision-language models (VLMs) have demonstrated remarkable capabilities in understanding and generating textual descriptions for visual content. However, these m…
Implicit Style-Content Separation using B-LoRA
Yarden Frenkel, Yael Vinker, Ariel Shamir +1
Image stylization involves manipulating the visual appearance and texture (style) of an image while preserving its underlying objects, structures, and concepts (content). The separ…
Generating Non-Stationary Textures using Self-Rectification
Yang Zhou, Rongjun Xiao, Dani Lischinski +2
This paper addresses the challenge of example-based non-stationary texture synthesis. We introduce a novel twostep approach wherein users first modify a reference texture using sta…
GraphiMind: LLM-centric Interface for Information Graphics Design
Qirui Huang, Min Lu, Joel Lanir +3
Information graphics are pivotal in effective information dissemination and storytelling. However, creating such graphics is extremely challenging for non-professionals, since the…
PALP: Prompt Aligned Personalization of Text-to-Image Models
Moab Arar, Andrey Voynov, Amir Hertz +5
Content creators often aim to create personalized images using personal subjects that go beyond the capabilities of conventional text-to-image models. Additionally, they may want t…
Style Aligned Image Generation via Shared Attention
Amir Hertz, Andrey Voynov, Shlomi Fruchter +1
Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts. However, controlling thes…