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Positional Prompt Tuning for Efficient 3D Representation Learning

Positional Prompt Tuning for Efficient 3D Representation Learning

21 August 2024
Shaochen Zhang
Zekun Qi
Runpei Dong
Xiuxiu Bai
Xing Wei
ArXivPDFHTML

Papers citing "Positional Prompt Tuning for Efficient 3D Representation Learning"

5 / 5 papers shown
Title
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud
  Pre-training
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Renrui Zhang
Ziyu Guo
Rongyao Fang
Bingyan Zhao
Dong Wang
Yu Qiao
Hongsheng Li
Peng Gao
3DPC
156
241
0
28 May 2022
PointDistiller: Structured Knowledge Distillation Towards Efficient and
  Compact 3D Detection
PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection
Linfeng Zhang
Runpei Dong
Hung-Shuo Tai
Kaisheng Ma
3DPC
55
42
0
23 May 2022
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
275
3,784
0
18 Apr 2021
PointContrast: Unsupervised Pre-training for 3D Point Cloud
  Understanding
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Saining Xie
Jiatao Gu
Demi Guo
C. Qi
Leonidas J. Guibas
Or Litany
3DPC
128
618
0
21 Jul 2020
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
210
13,886
0
02 Dec 2016
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