Summary

This individual’s research and experience centers around computer vision, deep learning, and robotics, particularly with applications in autonomous driving and cloud infrastructure. Their work includes research on image deburring, video synchronization, transfer learning for material classification, and efficient approximate nearest neighbor search on GPUs. Key projects and publications include “End-to-End Learning for Image Burst Deblurring” presented at ACCV 2016, alongside contributions to “Efficient Large-scale Approximate Nearest Neighbor Search on the GPU” at CVPR 2016. They’ve held research positions at Amazon, NVIDIA, and the Fraunhofer Institute IVI, with a Ph.D. from the University of Tübingen and Max Planck Institute, specializing in machine learning and massively parallel computing. Recent work was published in IEEE Transactions on Big Data in 2022, focusing on a deburring result.

Title

Patrick Wieschollek

Description

Patrick Wieschollek

Keywords

learning, computer, vision, patrick, data, conference, image, approach, video, machine, search, images, copy, code, neighbor, applications, networks

NS Lookup

A 185.199.111.153, A 185.199.109.153, A 185.199.110.153

Dates

Created 2026-03-08

Updated 2026-03-08

Summarized 2026-03-08