ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2410.10775
  4. Cited By
Browsing without Third-Party Cookies: What Do You See?

Browsing without Third-Party Cookies: What Do You See?

14 October 2024
Maxwell Lin
Shihan Lin
Helen Wu
Karen Wang
Xiaowei Yang
    BDL
ArXiv (abs)PDFHTML

Papers citing "Browsing without Third-Party Cookies: What Do You See?"

15 / 115 papers shown
Title
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in
  Semantic Segmentation
ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation
Tuan-Hung Vu
Himalaya Jain
Max Bucher
Matthieu Cord
P. Pérez
133
1,301
0
30 Nov 2018
Deep Co-Training for Semi-Supervised Image Recognition
Deep Co-Training for Semi-Supervised Image Recognition
Siyuan Qiao
Wei Shen
Zhishuai Zhang
Bo Wang
Alan Yuille
64
451
0
15 Mar 2018
Improved Regularization of Convolutional Neural Networks with Cutout
Improved Regularization of Convolutional Neural Networks with Cutout
Terrance Devries
Graham W. Taylor
137
3,775
0
15 Aug 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
803
132,454
0
12 Jun 2017
Deep Mutual Learning
Deep Mutual Learning
Ying Zhang
Tao Xiang
Timothy M. Hospedales
Huchuan Lu
FedML
155
1,656
0
01 Jun 2017
Virtual Adversarial Training: A Regularization Method for Supervised and
  Semi-Supervised Learning
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato
S. Maeda
Masanori Koyama
S. Ishii
GAN
153
2,739
0
13 Apr 2017
Pyramid Scene Parsing Network
Pyramid Scene Parsing Network
Hengshuang Zhao
Jianping Shi
Xiaojuan Qi
Xiaogang Wang
Jiaya Jia
VOSSSeg
665
12,035
0
04 Dec 2016
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDEBDLPINN
1.4K
14,618
0
07 Oct 2016
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets,
  Atrous Convolution, and Fully Connected CRFs
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
273
18,284
0
02 Jun 2016
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOSSSeg
750
37,895
0
20 May 2016
Training Region-based Object Detectors with Online Hard Example Mining
Training Region-based Object Detectors with Online Hard Example Mining
Abhinav Shrivastava
Abhinav Gupta
Ross B. Girshick
ObjD
157
2,422
0
12 Apr 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
1.1K
11,654
0
06 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,510
0
10 Dec 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,529
0
04 Sep 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
434
43,832
0
01 May 2014
Previous
123