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PooDLe: Pooled and dense self-supervised learning from naturalistic videos

PooDLe: Pooled and dense self-supervised learning from naturalistic videos

20 August 2024
Alex N. Wang
Christopher Hoang
Yuwen Xiong
Yann LeCun
Mengye Ren
ArXivPDFHTML

Papers citing "PooDLe: Pooled and dense self-supervised learning from naturalistic videos"

5 / 5 papers shown
Title
Guess What Moves: Unsupervised Video and Image Segmentation by
  Anticipating Motion
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion
Subhabrata Choudhury
Laurynas Karazija
Iro Laina
Andrea Vedaldi
Christian Rupprecht
OCL
VOS
100
39
0
16 May 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
255
7,337
0
11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
283
5,723
0
29 Apr 2021
Feature Pyramid Networks for Object Detection
Feature Pyramid Networks for Object Detection
Tsung-Yi Lin
Piotr Dollár
Ross B. Girshick
Kaiming He
Bharath Hariharan
Serge J. Belongie
ObjD
154
3,574
0
09 Dec 2016
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg
3DV
229
74,467
0
18 May 2015
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