activity
20142024
most citedIn Teacher We Trust: Learning Compressed Models for Pedestrian Detection

21 citations · 64 across the 16 of their papers we have counts for

collaborators

7 papers

cs.CV2023

TFormer: A Transmission-Friendly ViT Model for IoT Devices

Zhichao Lu, Chuntao Ding, Felix Juefei-Xu +3

Deploying high-performance vision transformer (ViT) models on ubiquitous Internet of Things (IoT) devices to provide high-quality vision services will revolutionize the way we live…

cs.LG2022

NeuralSI: Structural Parameter Identification in Nonlinear Dynamical Systems

Xuyang Li, Hamed Bolandi, Talal Salem +2

Structural monitoring for complex built environments often suffers from mismatch between design, laboratory testing, and actual built parameters. Additionally, real-world structura…

cs.CV2022

HEFT: Homomorphically Encrypted Fusion of Biometric Templates

Luke Sperling, Nalini Ratha, Arun Ross +1

This paper proposes a non-interactive end-to-end solution for secure fusion and matching of biometric templates using fully homomorphic encryption (FHE). Given a pair of encrypted…

cs.CV2021

Generating Diverse 3D Reconstructions from a Single Occluded Face Image

Rahul Dey, Vishnu Naresh Boddeti

Occlusions are a common occurrence in unconstrained face images. Single image 3D reconstruction from such face images often suffers from corruption due to the presence of occlusion…

cs.CV20169 cited

Visual Compiler: Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator

Namhoon Lee, Xinshuo Weng, Vishnu Naresh Boddeti +4

We introduce the concept of a Visual Compiler that generates a scene specific pedestrian detector and pose estimator without any pedestrian observations. Given a single image and a…

cs.CV201621 cited

In Teacher We Trust: Learning Compressed Models for Pedestrian Detection

Jonathan Shen, Noranart Vesdapunt, Vishnu N. Boddeti +1

Deep convolutional neural networks continue to advance the state-of-the-art in many domains as they grow bigger and more complex. It has been observed that many of the parameters o…