activity
20172021
most citedDeep Hyperspherical Learning

56 citations · 67 across the 3 of their papers we have counts for

collaborators

12 papers

cs.CV2021

Self-Supervised 3D Face Reconstruction via Conditional Estimation

Yandong Wen, Weiyang Liu, Bhiksha Raj +1

We present a conditional estimation (CEST) framework to learn 3D facial parameters from 2D single-view images by self-supervised training from videos. CEST is based on the process…

cs.LG2019

Angular Visual Hardness

Beidi Chen, Weiyang Liu, Zhiding Yu +4

Recent convolutional neural networks (CNNs) have led to impressive performance but often suffer from poor calibration. They tend to be overconfident, with the model confidence not…

cs.LG201911 cited

Neural Similarity Learning

Weiyang Liu, Zhen Liu, James M. Rehg +1

Inner product-based convolution has been the founding stone of convolutional neural networks (CNNs), enabling end-to-end learning of visual representation. By generalizing inner pr…

cs.CV2019

Regularizing Neural Networks via Minimizing Hyperspherical Energy

Rongmei Lin, Weiyang Liu, Zhen Liu +5

Inspired by the Thomson problem in physics where the distribution of multiple propelling electrons on a unit sphere can be modeled via minimizing some potential energy, hyperspheri…

cs.LG2018

Meta Architecture Search

Albert Shaw, Wei Wei, Weiyang Liu +2

Neural Architecture Search (NAS) has been quite successful in constructing state-of-the-art models on a variety of tasks. Unfortunately, the computational cost can make it difficul…

cs.CV2018

Simultaneous Edge Alignment and Learning

Zhiding Yu, Weiyang Liu, Yang Zou +4

Edge detection is among the most fundamental vision problems for its role in perceptual grouping and its wide applications. Recent advances in representation learning have led to c…