6 papers
ConCAD: Constraint-Aware Image-to-CAD Generation with Dual-Granularity Rewards
Chenxi Zhai, Xi Cheng, Hang Cheng +5
Image-to-CAD generation seeks executable parametric programs that recover both the geometry and design intent of a reference object. Existing systems are commonly evaluated by vali…
DIP-CAD: A Design-Intent-Preserving Agent Harness for Parametric CAD Modeling
Xi Cheng, Chenxi Zhai, Hang Cheng +3
Parametric CAD modeling requires not only matching the target shape, but also preserving design intent under parameter edits. However, most existing methods focus on improving stat…
Refine Then Fusion: Training-Free 3D Point Cloud Adaptation with Priority Refinement and Multi-Modal Knowledge Fusion
Hang Cheng, Yan Chen, Mingyu Fan +1
Recent pre-trained foundation models provide rich multi-modal priors for downstream 3D vision tasks. However, the effectiveness of these representations in few-shot scenarios is li…
WISE: World-model-guided Imagination Scheduling for Efficient Post-training of Vision-Language-Action Models
Chenhao Zhang, Hanyu Zhao, Hang Cheng +2
Post-training VLA policies typically rely on supervised fine-tuning with costly expert demonstrations or reinforcement learning with expensive and potentially unstable real-world e…
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…