ResearchTrend.AI
Learning Online Visual Invariances for Novel Objects via Supervised and Self-Supervised Training

Learning Online Visual Invariances for Novel Objects via Supervised and Self-Supervised Training

Valerio Biscione
J. Bowers
ArXivPDFHTML

Papers citing "Learning Online Visual Invariances for Novel Objects via Supervised and Self-Supervised Training"

4 / 4 papers shown
Title
Neither hype nor gloom do DNNs justice
Neither hype nor gloom do DNNs justice
Gaurav Malhotra
Christian Tsvetkov
B. D. Evans
21
117
0
08 Dec 2023
Improving Fine-tuning of Self-supervised Models with Contrastive Initialization
Improving Fine-tuning of Self-supervised Models with Contrastive Initialization
Haolin Pan
Yong Guo
Qinyi Deng
Hao-Fan Yang
Yiqun Chen
Jian Chen
SSL
18
19
0
30 Jul 2022
Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be
Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be
Valerio Biscione
J. Bowers
OOD
65
32
0
12 Oct 2021
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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
14,103
0
02 Dec 2016