From Zero-shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis

CVPR 2017 Yang LongLi LiuLing ShaoFumin ShenGuiguang DingJungong Han

Robust object recognition systems usually rely on powerful feature extraction mechanisms from a large number of real images. However, in many realistic applications, collecting sufficient images for ever-growing new classes is unattainable... (read more)

PDF Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.