Publications (7)
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…
Convolutional dual graph Laplacian sparse coding
Xuefeng Peng, Fei Chen, Hang Cheng +1
In recent years, graph signal processing (GSP) technology has become popular in various fields, and graph Laplacian regularizers have also been introduced into convolutional sparse…
A Two-grid Method for Linearizing and Symmetrizing the Steady-state Poisson-Nernst-Planck Equations
Xuefang Li, Ying Yang, Hang Cheng
In this paper, a two-grid method is proposed to linearize and symmetrize the steady-state Poisson-Nernst-Planck equations. The computational system is decoupled to linearize and sy…
Step-GUI Technical Report
Haolong Yan, Jia Wang, Xin Huang +95
Recent advances in multimodal large language models unlock unprecedented opportunities for GUI automation. However, a fundamental challenge remains: how to efficiently acquire high…
SDGraph: Multi-Level Sketch Representation Learning by Sparse-Dense Graph Architecture
Xi Cheng, Pingfa Feng, Mingyu Fan +3
Freehand sketches exhibit unique sparsity and abstraction, necessitating learning pipelines distinct from those designed for images. For sketch learning methods, the central object…