Staying in Shape: Learning Invariant Shape Representations using Contrastive Learning

8 July 2021

Papers citing "Staying in Shape: Learning Invariant Shape Representations using Contrastive Learning"

8 / 8 papers shown

Title
Advancing Perception in Artificial Intelligence through Principles of Cognitive Science Palaash Agrawal Cheston Tan Heena Rathore 57 1 0 13 Oct 2023
A Simple Strategy to Provable Invariance via Orbit Mapping Kanchana Vaishnavi Gandikota Jonas Geiping Zorah Lähner Adam Czapliñski Michael Moeller AAML 3DPC 18 3 0 24 Sep 2022
Addressing Token Uniformity in Transformers via Singular Value Transformation Hanqi Yan Lin Gui Wenjie Li Yulan He 35 14 0 24 Aug 2022
Upsampling Autoencoder for Self-Supervised Point Cloud Learning Cheng Zhang Jian Shi X. Deng Zizhao Wu 3DPC 27 8 0 21 Mar 2022
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding Saining Xie Jiatao Gu Demi Guo C. Qi Leonidas J. Guibas Or Litany 3DPC 141 624 0 21 Jul 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 281 3,378 0 09 Mar 2020
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,131 0 02 Dec 2016
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling Jiajun Wu Chengkai Zhang Tianfan Xue Bill Freeman J. Tenenbaum GAN 191 1,942 0 24 Oct 2016