no code implementations • 25 Aug 2023 • Mei-Yuh Hwang, Yangyang Shi, Ankit Ramchandani, Guan Pang, Praveen Krishnan, Lucas Kabela, Frank Seide, Samyak Datta, Jun Liu
This paper discusses the challenges of optical character recognition (OCR) on natural scenes, which is harder than OCR on documents due to the wild content and various image backgrounds.
1 code implementation • 15 Jun 2021 • Praveen Krishnan, Rama Kovvuri, Guan Pang, Boris Vassilev, Tal Hassner
We present a novel approach for disentangling the content of a text image from all aspects of its appearance.
1 code implementation • CVPR 2021 • Jing Huang, Guan Pang, Rama Kovvuri, Mandy Toh, Kevin J Liang, Praveen Krishnan, Xi Yin, Tal Hassner
Recent advances in OCR have shown that an end-to-end (E2E) training pipeline that includes both detection and recognition leads to the best results.
1 code implementation • 27 Oct 2020 • Siddhant Bansal, Praveen Krishnan, C. V. Jawahar
We propose a novel scheme for improving the word recognition accuracy using word image embeddings.
1 code implementation • 1 Jul 2020 • Siddhant Bansal, Praveen Krishnan, C. V. Jawahar
Recognition and retrieval of textual content from the large document collections have been a powerful use case for the document image analysis community.
no code implementations • 17 Feb 2018 • Praveen Krishnan, C. V. Jawahar
We present a framework for learning an efficient holistic representation for handwritten word images.
1 code implementation • 15 Aug 2016 • Praveen Krishnan, C. V. Jawahar
Generating synthetic images is an art which emulates the natural process of image generation in a closest possible manner.
no code implementations • 19 May 2016 • Praveen Krishnan, C. V. Jawahar
We address the problem of predicting similarity between a pair of handwritten document images written by different individuals.