activity
20212023
most citedDEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection

4 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

FOCAL: A Cost-Aware Video Dataset for Active Learning

Kiran Kokilepersaud, Yash-Yee Logan, Ryan Benkert +6

In this paper, we introduce the FOCAL (Ford-OLIVES Collaboration on Active Learning) dataset which enables the study of the impact of annotation-cost within a video active learning…

cs.LG2023

Gaussian Switch Sampling: A Second Order Approach to Active Learning

Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib +2

In active learning, acquisition functions define informativeness directly on the representation position within the model manifold. However, for most machine learning models (in pa…

cs.CV2022★ 4 cited

DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object Detection

Abhinav Kumar, Garrick Brazil, Enrique Corona +2

Modern neural networks use building blocks such as convolutions that are equivariant to arbitrary 2D translations. However, these vanilla blocks are not equivariant to arbitrary 3D…

cs.RO2021

Localization of a Smart Infrastructure Fisheye Camera in a Prior Map for Autonomous Vehicles

Subodh Mishra, Armin Parchami, Enrique Corona +4

This work presents a technique for localization of a smart infrastructure node, consisting of a fisheye camera, in a prior map. These cameras can detect objects that are outside th…

cs.CV2021★ 1 cited

Efficient data-driven encoding of scene motion using Eccentricity

Bruno Costa, Enrique Corona, Mostafa Parchami +2

This paper presents a novel approach of representing dynamic visual scenes with static maps generated from video/image streams. Such representation allows easy visual assessment of…