Disentangling 3D Prototypical Networks For Few-Shot Concept Learning

6 November 2020

Papers citing "Disentangling 3D Prototypical Networks For Few-Shot Concept Learning"

8 / 8 papers shown

Title
Explicitly Disentangled Representations in Object-Centric Learning Riccardo Majellaro Jonathan Collu Aske Plaat Thomas M. Moerland CoGe OOD OCL 68 1 0 18 Jan 2024
Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization Stefan Stojanov Anh Thai Zixuan Huang James M. Rehg 33 1 0 28 Nov 2022
Disentangled Representation Learning Xin Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 35 78 0 21 Nov 2022
Neural Systematic Binder Gautam Singh Yeongbin Kim Sungjin Ahn OCL 32 36 0 02 Nov 2022
Active Transfer Prototypical Network: An Efficient Labeling Algorithm for Time-Series Data Yuqi Zhu M. Tnani Timo Jahnz Klaus Diepold 13 0 0 28 Sep 2022
Contributions of Shape, Texture, and Color in Visual Recognition Yunhao Ge Yao Xiao Zhi-Qin John Xu X. Wang Laurent Itti 3DH 16 26 0 19 Jul 2022
Video Autoencoder: self-supervised disentanglement of static 3D structure and motion Zihang Lai Sifei Liu Alexei A. Efros Xiaolong Wang VGen 36 31 0 06 Oct 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 300 10,368 0 12 Dec 2018