Disentangling 3D Prototypical Networks For Few-Shot Concept Learning

6 November 2020

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

9 / 9 papers shown

Title
Explicitly Disentangled Representations in Object-Centric Learning Riccardo Majellaro Jonathan Collu Aske Plaat Thomas M. Moerland CoGe OOD OCL 76 1 0 18 Jan 2024
Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason? Monika Wysoczañska Tom Monnier Tomasz Trzciñski David Picard ReLM OCL 40 1 0 20 Dec 2022
Learning Dense Object Descriptors from Multiple Views for Low-shot Category Generalization Stefan Stojanov Anh Thai Zixuan Huang James M. Rehg 39 1 0 28 Nov 2022
Disentangled Representation Learning Xin Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 37 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 41 31 0 06 Oct 2021
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 306 10,378 0 12 Dec 2018