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Where Should I Spend My FLOPS? Efficiency Evaluations of Visual
  Pre-training Methods

Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods

30 September 2022
Skanda Koppula
Yazhe Li
Evan Shelhamer
Andrew Jaegle
Nikhil Parthasarathy
Relja Arandjelović
João Carreira
Olivier J. Hénaff
ArXivPDFHTML

Papers citing "Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods"

14 / 14 papers shown
Title
HYPE: Hyperbolic Entailment Filtering for Underspecified Images and
  Texts
HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts
Wonjae Kim
Sanghyuk Chun
Taekyung Kim
Dongyoon Han
Sangdoo Yun
39
7
0
26 Apr 2024
How to Scale Your EMA
How to Scale Your EMA
Dan Busbridge
Jason Ramapuram
Pierre Ablin
Tatiana Likhomanenko
Eeshan Gunesh Dhekane
Xavier Suau
Russ Webb
25
17
0
25 Jul 2023
Improving CLIP Training with Language Rewrites
Improving CLIP Training with Language Rewrites
Lijie Fan
Dilip Krishnan
Phillip Isola
Dina Katabi
Yonglong Tian
BDL
VLM
CLIP
24
155
0
31 May 2023
End-to-End Spatio-Temporal Action Localisation with Video Transformers
End-to-End Spatio-Temporal Action Localisation with Video Transformers
A. Gritsenko
Xuehan Xiong
Josip Djolonga
Mostafa Dehghani
Chen Sun
Mario Lucic
Cordelia Schmid
Anurag Arnab
ViT
32
13
0
24 Apr 2023
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised
  Learning of Actions
HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of Actions
Anshul B. Shah
A. Roy
Ketul Shah
Shlok Kumar Mishra
David W. Jacobs
A. Cherian
Ramalingam Chellappa
SSL
19
25
0
01 Apr 2023
Reproducible scaling laws for contrastive language-image learning
Reproducible scaling laws for contrastive language-image learning
Mehdi Cherti
Romain Beaumont
Ross Wightman
Mitchell Wortsman
Gabriel Ilharco
Cade Gordon
Christoph Schuhmann
Ludwig Schmidt
J. Jitsev
VLM
CLIP
51
737
0
14 Dec 2022
Location-Aware Self-Supervised Transformers for Semantic Segmentation
Location-Aware Self-Supervised Transformers for Semantic Segmentation
Mathilde Caron
N. Houlsby
Cordelia Schmid
ViT
18
10
0
05 Dec 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
305
7,434
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
314
5,775
0
29 Apr 2021
ImageNet-21K Pretraining for the Masses
ImageNet-21K Pretraining for the Masses
T. Ridnik
Emanuel Ben-Baruch
Asaf Noy
Lihi Zelnik-Manor
SSeg
VLM
CLIP
176
686
0
22 Apr 2021
High-Performance Large-Scale Image Recognition Without Normalization
High-Performance Large-Scale Image Recognition Without Normalization
Andrew Brock
Soham De
Samuel L. Smith
Karen Simonyan
VLM
223
512
0
11 Feb 2021
BYOL works even without batch statistics
BYOL works even without batch statistics
Pierre Harvey Richemond
Jean-Bastien Grill
Florent Altché
Corentin Tallec
Florian Strub
...
Samuel L. Smith
Soham De
Razvan Pascanu
Bilal Piot
Michal Valko
SSL
250
114
0
20 Oct 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
228
4,460
0
23 Jan 2020
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
296
39,194
0
01 Sep 2014
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