1 code implementation • CVPR 2023 • Vignesh Ramanathan, Anmol Kalia, Vladan Petrovic, Yi Wen, Baixue Zheng, Baishan Guo, Rui Wang, Aaron Marquez, Rama Kovvuri, Abhishek Kadian, Amir Mousavi, Yiwen Song, Abhimanyu Dubey, Dhruv Mahajan
This motivates the need for large datasets which go beyond traditional object masks and provide richer annotations such as part masks and attributes.
no code implementations • ICCV 2023 • Peri Akiva, Jing Huang, Kevin J Liang, Rama Kovvuri, Xingyu Chen, Matt Feiszli, Kristin Dana, Tal Hassner
Understanding the visual world from the perspective of humans (egocentric) has been a long-standing challenge in computer vision.
1 code implementation • 13 Oct 2022 • Jing Huang, Kevin J Liang, Rama Kovvuri, Tal Hassner
Most existing OCR methods focus on alphanumeric characters due to the popularity of English and numbers, as well as their corresponding datasets.
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.
no code implementations • 7 Dec 2018 • Rama Kovvuri, Ram Nevatia
Phrase Grounding aims to detect and localize objects in images that are referred to and are queried by natural language phrases.
no code implementations • ICCV 2017 • Kan Chen, Rama Kovvuri, Ram Nevatia
Given a textual description of an image, phrase grounding localizes objects in the image referred by query phrases in the description.