activity
20182021
most citedSMART: Simultaneous Multi-Agent Recurrent Trajectory Prediction

2 citations · 2 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CV2021

Divide-and-Conquer for Lane-Aware Diverse Trajectory Prediction

Sriram Narayanan, Ramin Moslemi, Francesco Pittaluga +2

Trajectory prediction is a safety-critical tool for autonomous vehicles to plan and execute actions. Our work addresses two key challenges in trajectory prediction, learning multim…

cs.LG2020

Voting-based Approaches For Differentially Private Federated Learning

Yuqing Zhu, Xiang Yu, Yi-Hsuan Tsai +4

Differentially Private Federated Learning (DPFL) is an emerging field with many applications. Gradient averaging based DPFL methods require costly communication rounds and hardly w…

cs.CV20202 cited

SMART: Simultaneous Multi-Agent Recurrent Trajectory Prediction

Sriram N N, Buyu Liu, Francesco Pittaluga +1

We propose advances that address two key challenges in future trajectory prediction: (i) multimodality in both training data and predictions and (ii) constant time inference regard…

cs.CV2020

Towards a MEMS-based Adaptive LIDAR

Francesco Pittaluga, Zaid Tasneem, Justin Folden +3

We present a proof-of-concept LIDAR design that allows adaptive real-time measurements according to dynamically specified measurement patterns. We describe our optical setup and ca…

cs.CV2019

Revealing Scenes by Inverting Structure from Motion Reconstructions

Francesco Pittaluga, Sanjeev J. Koppal, Sing Bing Kang +1

Many 3D vision systems localize cameras within a scene using 3D point clouds. Such point clouds are often obtained using structure from motion (SfM), after which the images are dis…

cs.CV2019

Privacy-Preserving Action Recognition using Coded Aperture Videos

Zihao W. Wang, Vibhav Vineet, Francesco Pittaluga +3

The risk of unauthorized remote access of streaming video from networked cameras underlines the need for stronger privacy safeguards. We propose a lens-free coded aperture camera s…