12 citations · 25 across the 7 of their papers we have counts for
10 papers
Adapting CLIP For Phrase Localization Without Further Training
Jiahao Li, Greg Shakhnarovich, Raymond A. Yeh
Supervised or weakly supervised methods for phrase localization (textual grounding) either rely on human annotations or some other supervised models, e.g., object detectors. Obtain…
Searching for fingerspelled content in American Sign Language
Bowen Shi, Diane Brentari, Greg Shakhnarovich +1
Natural language processing for sign language video - including tasks like recognition, translation, and search - is crucial for making artificial intelligence technologies accessi…
Neural Neighbor Style Transfer
Nicholas Kolkin, Michal Kucera, Sylvain Paris +3
We propose Neural Neighbor Style Transfer (NNST), a pipeline that offers state-of-the-art quality, generalization, and competitive efficiency for artistic style transfer. Our appro…
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness
Avrim Blum, Omar Montasser, Greg Shakhnarovich +1
We present an oracle-efficient algorithm for boosting the adversarial robustness of barely robust learners. Barely robust learning algorithms learn predictors that are adversariall…
Fingerspelling Detection in American Sign Language
Bowen Shi, Diane Brentari, Greg Shakhnarovich +1
Fingerspelling, in which words are signed letter by letter, is an important component of American Sign Language. Most previous work on automatic fingerspelling recognition has assu…
Full Surround Monodepth from Multiple Cameras
Vitor Guizilini, Igor Vasiljevic, Rares Ambrus +2
Self-supervised monocular depth and ego-motion estimation is a promising approach to replace or supplement expensive depth sensors such as LiDAR for robotics applications like auto…