316 citations · 719 across the 29 of their papers we have counts for
38 papers · 1 filter
CLIPXPlore: Coupled CLIP and Shape Spaces for 3D Shape Exploration
Jingyu Hu, Ka-Hei Hui, Zhengzhe liu +2
This paper presents CLIPXPlore, a new framework that leverages a vision-language model to guide the exploration of the 3D shape space. Many recent methods have been developed to en…
Sparse2Dense: Learning to Densify 3D Features for 3D Object Detection
Tianyu Wang, Xiaowei Hu, Zhengzhe Liu +1
LiDAR-produced point clouds are the major source for most state-of-the-art 3D object detectors. Yet, small, distant, and incomplete objects with sparse or few points are often hard…
Neural Wavelet-domain Diffusion for 3D Shape Generation
Ka-Hei Hui, Ruihui Li, Jingyu Hu +1
This paper presents a new approach for 3D shape generation, enabling direct generative modeling on a continuous implicit representation in wavelet domain. Specifically, we propose…
Towards Implicit Text-Guided 3D Shape Generation
Zhengzhe Liu, Yi Wang, Xiaojuan Qi +1
In this work, we explore the challenging task of generating 3D shapes from text. Beyond the existing works, we propose a new approach for text-guided 3D shape generation, capable o…
Towards Robust Part-aware Instance Segmentation for Industrial Bin Picking
Yidan Feng, Biqi Yang, Xianzhi Li +7
Industrial bin picking is a challenging task that requires accurate and robust segmentation of individual object instances. Particularly, industrial objects can have irregular shap…
Point Set Self-Embedding
Ruihui Li, Xianzhi Li, Tien-Tsin Wong +1
This work presents an innovative method for point set self-embedding, that encodes the structural information of a dense point set into its sparser version in a visual but impercep…