activity
20182026
most citedLocally Attentional SDF Diffusion for Controllable 3D Shape Generation

120 citations · 227 across the 12 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CV2023

SAMPro3D: Locating SAM Prompts in 3D for Zero-Shot Instance Segmentation

Mutian Xu, Xingyilang Yin, Lingteng Qiu +3

We introduce SAMPro3D for zero-shot instance segmentation of 3D scenes. Given the 3D point cloud and multiple posed RGB-D frames of 3D scenes, our approach segments 3D instances by…

cs.CV2023

StructRe: Rewriting for Structured Shape Modeling

Jiepeng Wang, Hao Pan, Yang Liu +3

Man-made 3D shapes are naturally organized in parts and hierarchies; such structures provide important constraints for shape reconstruction and generation. Modeling shape structure…

cs.CV2023120 cited

Locally Attentional SDF Diffusion for Controllable 3D Shape Generation

Xin-Yang Zheng, Hao Pan, Peng-Shuai Wang +3

Although the recent rapid evolution of 3D generative neural networks greatly improves 3D shape generation, it is still not convenient for ordinary users to create 3D shapes and con…

cs.CV2023

3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining

Siming Yan, Yuqi Yang, Yuxiao Guo +5

Masked autoencoders (MAE) have recently been introduced to 3D self-supervised pretraining for point clouds due to their great success in NLP and computer vision. Unlike MAEs used i…

cs.CV2023

Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding

Yu-Qi Yang, Yu-Xiao Guo, Jian-Yu Xiong +5

The use of pretrained backbones with fine-tuning has been successful for 2D vision and natural language processing tasks, showing advantages over task-specific networks. In this wo…