1 citations · 1 across the 3 of their papers we have counts for
6 papers
GeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation
Ken Deng, Yunhan Yang, Jingxiang Sun +4
We introduce GeoSAM2, a prompt-controllable framework for 3D part segmentation that casts the task as multi-view 2D mask prediction. Given a textureless object, we render normal an…
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
Yunhan Yang, Yufan Zhou, Yuan-Chen Guo +7
The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, lim…
DreamComposer++: Empowering Diffusion Models with Multi-View Conditions for 3D Content Generation
Yunhan Yang, Shuo Chen, Yukun Huang +6
Recent advancements in leveraging pre-trained 2D diffusion models achieve the generation of high-quality novel views from a single in-the-wild image. However, existing works face c…
HoloPart: Generative 3D Part Amodal Segmentation
Yunhan Yang, Yuan-Chen Guo, Yukun Huang +5
3D part amodal segmentation--decomposing a 3D shape into complete, semantically meaningful parts, even when occluded--is a challenging but crucial task for 3D content creation and…
MIDI: Multi-Instance Diffusion for Single Image to 3D Scene Generation
Zehuan Huang, Yuan-Chen Guo, Xingqiao An +7
This paper introduces MIDI, a novel paradigm for compositional 3D scene generation from a single image. Unlike existing methods that rely on reconstruction or retrieval techniques…
SAMPart3D: Segment Any Part in 3D Objects
Yunhan Yang, Yukun Huang, Yuan-Chen Guo +5
3D part segmentation is a crucial and challenging task in 3D perception, playing a vital role in applications such as robotics, 3D generation, and 3D editing. Recent methods harnes…