The Second Monocular Depth Estimation Challenge

no code implementations • 14 Apr 2023 • Jaime Spencer, C. Stella Qian, Michaela Trescakova, Chris Russell, Simon Hadfield, Erich W. Graf, Wendy J. Adams, Andrew J. Schofield, James Elder, Richard Bowden, Ali Anwar, Hao Chen, Xiaozhi Chen, Kai Cheng, Yuchao Dai, Huynh Thai Hoa, Sadat Hossain, Jianmian Huang, Mohan Jing, Bo Li, Chao Li, Baojun Li, Zhiwen Liu, Stefano Mattoccia, Siegfried Mercelis, Myungwoo Nam, Matteo Poggi, Xiaohua Qi, Jiahui Ren, Yang Tang, Fabio Tosi, Linh Trinh, S. M. Nadim Uddin, Khan Muhammad Umair, Kaixuan Wang, YuFei Wang, Yixing Wang, Mochu Xiang, Guangkai Xu, Wei Yin, Jun Yu, Qi Zhang, Chaoqiang Zhao

This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC).

Monocular Depth Estimation

Fast Charging of Lithium-Ion Batteries Using Deep Bayesian Optimization with Recurrent Neural Network

no code implementations • 9 Apr 2023 • Benben Jiang, Yixing Wang, Zhenghua Ma, Qiugang Lu

Fast charging has attracted increasing attention from the battery community for electrical vehicles (EVs) to alleviate range anxiety and reduce charging time for EVs.

Bayesian Optimization

Scene Synthesis from Human Motion

no code implementations • 4 Jan 2023 • Sifan Ye, Yixing Wang, Jiaman Li, Dennis Park, C. Karen Liu, Huazhe Xu, Jiajun Wu

Large-scale capture of human motion with diverse, complex scenes, while immensely useful, is often considered prohibitively costly.

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design

no code implementations • 4 Jul 2019 • Akshay Iyer, Yichi Zhang, Aditya Prasad, Siyu Tao, Yixing Wang, Linda Schadler, L Catherine Brinson, Wei Chen

To this end, we present a data-centric, mixed-variable Bayesian Optimization framework that integrates data from literature, experiments, and simulations for knowledge discovery and computational materials design.

Bayesian Optimization Navigate