5 papers
PureCC: Pure Learning for Text-to-Image Concept Customization
Zhichao Liao, Xiaole Xian, Qingyu Li +7
Existing concept customization methods have achieved remarkable outcomes in high-fidelity and multi-concept customization. However, they often neglect the influence on the original…
Diff-SBSR: Learning Multimodal Feature-Enhanced Diffusion Models for Zero-Shot Sketch-Based 3D Shape Retrieval
Hang Cheng, Fanhe Dong, Long Zeng
This paper presents the first exploration of text-to-image diffusion models for zero-shot sketch-based 3D shape retrieval (ZS-SBSR). Existing sketch-based 3D shape retrieval method…
Multi-View Hierarchical Graph Neural Network for Sketch-Based 3D Shape Retrieval
Hang Cheng, Muyan He, Mingyu Fan +3
Sketch-based 3D shape retrieval (SBSR) aims to retrieve 3D shapes that are consistent with the category of the input hand-drawn sketch. The core challenge of this task lies in two…
HumanAesExpert: Advancing a Multi-Modality Foundation Model for Human Image Aesthetic Assessment
Zhichao Liao, Xiaokun Liu, Wenyu Qin +6
Image Aesthetic Assessment (IAA) is a long-standing and challenging research task. However, its subset, Human Image Aesthetic Assessment (HIAA), has been scarcely explored. To brid…
SPF-Portrait: Towards Pure Text-to-Portrait Customization with Semantic Pollution-Free Fine-Tuning
Xiaole Xian, Zhichao Liao, Qingyu Li +6
Fine-tuning a pre-trained Text-to-Image (T2I) model on a tailored portrait dataset is the mainstream method for text-to-portrait customization. However, existing methods often seve…