Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories

16 February 2020

Papers citing "Learning to Group: A Bottom-Up Framework for 3D Part Discovery in Unseen Categories"

8 / 8 papers shown

Title
ZeroPS: High-quality Cross-modal Knowledge Transfer for Zero-Shot 3D Part Segmentation Yuheng Xue Nenglun Chen Jun Liu Wenyun Sun 3DPC 77 7 0 24 Feb 2025
Rearrangement Planning for General Part Assembly Yulong Li Andy Zeng Shuran Song 31 9 0 01 Jul 2023
Seg&Struct: The Interplay Between Part Segmentation and Structure Inference for 3D Shape Parsing Jeonghyun Kim Kaichun Mo Minhyuk Sung Woontack Woo 3DPC 34 1 0 01 Nov 2022
LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery Chunfeng Yao Wei-Chih Hung Yuanzhen Li Michael Rubinstein Ming Yang Varun Jampani 3DV 34 47 0 07 Jul 2022
AutoGPart: Intermediate Supervision Search for Generalizable 3D Part Segmentation Xueyi Liu Xiaomeng Xu Anyi Rao Chuang Gan L. Yi 3DPC 26 14 0 13 Mar 2022
PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation Gopal Sharma Bidya Dash Aruni RoyChowdhury Matheus Gadelha Marios Loizou Liangliang Cao Rui Wang Erik Learned-Miller Subhransu Maji E. Kalogerakis 3DPC 27 13 0 27 Dec 2021
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning Yining Hong Li Yi J. Tenenbaum Antonio Torralba Chuang Gan 9 39 0 09 Dec 2021
Learning Fine-Grained Segmentation of 3D Shapes without Part Labels Xiaogang Wang Xun Sun Xinyu Cao Kai Xu Bin Zhou 3DV 3DPC 35 16 0 24 Mar 2021