12 citations · 29 across the 9 of their papers we have counts for
11 papers
Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields
Joshua Ahn, Haochen Wang, Raymond A. Yeh +1
Scale-ambiguity in 3D scene dimensions leads to magnitude-ambiguity of volumetric densities in neural radiance fields, i.e., the densities double when scene size is halved, and vic…
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…
Information-Theoretic Segmentation by Inpainting Error Maximization
Pedro Savarese, Sunnie S. Y. Kim, Michael Maire +2
We study image segmentation from an information-theoretic perspective, proposing a novel adversarial method that performs unsupervised segmentation by partitioning images into maxi…
Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion
Igor Vasiljevic, Vitor Guizilini, Rares Ambrus +4
Self-supervised learning has emerged as a powerful tool for depth and ego-motion estimation, leading to state-of-the-art results on benchmark datasets. However, one significant lim…
Controlling Length in Image Captioning
Ruotian Luo, Greg Shakhnarovich
We develop and evaluate captioning models that allow control of caption length. Our models can leverage this control to generate captions of different style and descriptiveness.
Fingerspelling recognition in the wild with iterative visual attention
Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane +3
Sign language recognition is a challenging gesture sequence recognition problem, characterized by quick and highly coarticulated motion. In this paper we focus on recognition of fi…