Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Leonid Karlinsky

Leonid Karlinsky
Alert button

A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning


Dec 16, 2019
Yunhui Guo, Noel C. F. Codella, Leonid Karlinsky, John R. Smith, Tajana Rosing, Rogerio Feris

Add code
Alert button

Figure 1 for A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning
Figure 2 for A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning
Figure 3 for A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning
Figure 4 for A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification


Dec 03, 2019
Sivan Doveh, Eli Schwartz, Chao Xue, Rogerio Feris, Alex Bronstein, Raja Giryes, Leonid Karlinsky

Add code
Alert button

Figure 1 for MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification
Figure 2 for MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification
Figure 3 for MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification
Figure 4 for MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Baby steps towards few-shot learning with multiple semantics


Jun 05, 2019
Eli Schwartz, Leonid Karlinsky, Rogerio Feris, Raja Giryes, Alex M. Bronstein

Add code
Alert button

Figure 1 for Baby steps towards few-shot learning with multiple semantics
Figure 2 for Baby steps towards few-shot learning with multiple semantics
Figure 3 for Baby steps towards few-shot learning with multiple semantics
Figure 4 for Baby steps towards few-shot learning with multiple semantics

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

LaSO: Label-Set Operations networks for multi-label few-shot learning


Feb 26, 2019
Amit Alfassy, Leonid Karlinsky, Amit Aides, Joseph Shtok, Sivan Harary, Rogerio Feris, Raja Giryes, Alex M. Bronstein

Add code
Alert button

Figure 1 for LaSO: Label-Set Operations networks for multi-label few-shot learning
Figure 2 for LaSO: Label-Set Operations networks for multi-label few-shot learning
Figure 3 for LaSO: Label-Set Operations networks for multi-label few-shot learning
Figure 4 for LaSO: Label-Set Operations networks for multi-label few-shot learning

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Co-regularized Alignment for Unsupervised Domain Adaptation


Nov 13, 2018
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogerio Feris, William T. Freeman, Gregory Wornell

Add code
Alert button

Figure 1 for Co-regularized Alignment for Unsupervised Domain Adaptation
Figure 2 for Co-regularized Alignment for Unsupervised Domain Adaptation
Figure 3 for Co-regularized Alignment for Unsupervised Domain Adaptation
Figure 4 for Co-regularized Alignment for Unsupervised Domain Adaptation
* NIPS 2018 accepted version 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

RepMet: Representative-based metric learning for classification and one-shot object detection


Jun 15, 2018
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Sharathchandra Pankanti, Rogerio Feris, Abhishek Kumar, Raja Giryes, Alex M. Bronstein

Add code
Alert button

Figure 1 for RepMet: Representative-based metric learning for classification and one-shot object detection
Figure 2 for RepMet: Representative-based metric learning for classification and one-shot object detection
Figure 3 for RepMet: Representative-based metric learning for classification and one-shot object detection
Figure 4 for RepMet: Representative-based metric learning for classification and one-shot object detection

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Delta-encoder: an effective sample synthesis method for few-shot object recognition


Jun 12, 2018
Eli Schwartz, Leonid Karlinsky, Joseph Shtok, Sivan Harary, Mattias Marder, Rogerio Feris, Abhishek Kumar, Raja Giryes, Alex M. Bronstein

Add code
Alert button

Figure 1 for Delta-encoder: an effective sample synthesis method for few-shot object recognition
Figure 2 for Delta-encoder: an effective sample synthesis method for few-shot object recognition
Figure 3 for Delta-encoder: an effective sample synthesis method for few-shot object recognition
Figure 4 for Delta-encoder: an effective sample synthesis method for few-shot object recognition

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
<<
1
2
3
4