TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	EXTRA DATA	REMOVE
Zero-Shot Learning	CUB-200 - 0-Shot Learning	zsl_ADA	Average Per-Class Accuracy	70.9	# 1

🦡 Badges

Include the markdown at the top of your GitHub README.md file to showcase the performance of the model.

Badges are live and will be dynamically updated with the latest ranking of this paper.

Badge	Markdown
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/a-generative-framework-for-zero-shot-learning/zero-shot-learning-on-cub-200-0-shot-learning-1)](https://paperswithcode.com/sota/zero-shot-learning-on-cub-200-0-shot-learning-1?p=a-generative-framework-for-zero-shot-learning)`

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation

7 Jun 2019 • Varun Khare • Divyat Mahajan • Homanga Bharadhwaj • Vinay Verma • Piyush Rai

We present a domain adaptation based generative framework for zero-shot learning. Our framework addresses the problem of domain shift between the seen and unseen class distributions in zero-shot learning and minimizes the shift by developing a generative model trained via adversarial domain adaptation... (read more)

PDF Abstract

Code

Add Remove Mark official

vkkhare/ZSL-ADA official

Tasks

Add Remove

DOMAIN ADAPTATION

ZERO-SHOT LEARNING

Results from the Paper

Edit

Ranked #1 on Zero-Shot Learning on CUB-200 - 0-Shot Learning (using extra training data)

Get a GitHub badge

TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	USES EXTRA TRAINING DATA	RESULT	BENCHMARK
Zero-Shot Learning	CUB-200 - 0-Shot Learning	zsl_ADA	Average Per-Class Accuracy	70.9	# 1			Compare

Methods used in the Paper

Add Remove

METHOD	TYPE
🤖 No Methods Found	Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet

A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Results from the Paper Edit

Methods used in the Paper Edit Add Remove

Code

Add Remove Mark official

Tasks

Add Remove

Results from the Paper

Edit

Methods used in the Paper

Add Remove