no code implementations • 25 Jan 2024 • Ruixuan Zhang, Wenyu Han, Zilin Bian, Kaan Ozbay, Chen Feng
We introduce a novel learning-based framework that strategically decides observation timings for battery-powered devices and reconstructs the full data stream from sparsely sampled observations, resulting in minimal performance loss and a significantly prolonged system lifetime.
no code implementations • 27 Sep 2023 • Wenyu Han, Congcong Wen, Lazarus Chok, Yan Liang Tan, Sheung Lung Chan, Hang Zhao, Chen Feng
Based on this dataset, we propose AETree, a tree-structured auto-encoder neural network, for city generation.
1 code implementation • 31 Mar 2021 • Wenyu Han, Chen Feng, Haoran Wu, Alexander Gao, Armand Jordana, Dong Liu, Lerrel Pinto, Ludovic Righetti
We need intelligent robots for mobile construction, the process of navigating in an environment and modifying its structure according to a geometric design.
no code implementations • 1 Jan 2021 • Congcong Wen, Wenyu Han, Hang Zhao, Chen Feng
Areal spatial data represent not only geographical locations but also sizes and shapes of physical objects such as buildings in a city.
no code implementations • 1 Jan 2021 • Wenyu Han, Chen Feng, Haoran Wu, Alexander Gao, Armand Jordana, Dongdong Liu, Lerrel Pinto, Ludovic Righetti
We need intelligent robots to perform mobile construction, the process of moving in an environment and modifying its geometry according to a design plan.
1 code implementation • CVPR 2020 • Wenyu Han, Siyuan Xiang, Chenhui Liu, Ruoyu Wang, Chen Feng
Our experiments show that although convolutional networks have achieved superhuman performance in many visual learning tasks, their spatial reasoning performance on SPARE3D tasks is either lower than average human performance or even close to random guesses.