activity
20152022
most citedLaplacian-Steered Neural Style Transfer

85 citations · 98 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV20228 cited

CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flow

Xiuchao Sui, Shaohua Li, Xue Geng +5

Optical flow estimation aims to find the 2D motion field by identifying corresponding pixels between two images. Despite the tremendous progress of deep learning-based optical flow…

cs.CV2020

Feature Lenses: Plug-and-play Neural Modules for Transformation-Invariant Visual Representations

Shaohua Li, Xiuchao Sui, Jie Fu +2

Convolutional Neural Networks (CNNs) are known to be brittle under various image transformations, including rotations, scalings, and changes of lighting conditions. We observe that…

cs.RO20195 cited

RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization

Tianying Wang, Wei Qi Toh, Hao Zhang +4

Robotic drawing has become increasingly popular as an entertainment and interactive tool. In this paper we present RoboCoDraw, a real-time collaborative robot-based drawing system…

cs.CV2019

Multi-Instance Multi-Scale CNN for Medical Image Classification

Shaohua Li, Yong Liu, Xiuchao Sui +4

Deep learning for medical image classification faces three major challenges: 1) the number of annotated medical images for training are usually small; 2) regions of interest (ROIs)…

cs.CV201785 cited

Laplacian-Steered Neural Style Transfer

Shaohua Li, Xinxing Xu, Liqiang Nie +1

Neural Style Transfer based on Convolutional Neural Networks (CNN) aims to synthesize a new image that retains the high-level structure of a content image, rendered in the low-leve…

cs.CL2017

Dirichlet-vMF Mixture Model

Shaohua Li

This document is about the multi-document Von-Mises-Fisher mixture model with a Dirichlet prior, referred to as VMFMix. VMFMix is analogous to Latent Dirichlet Allocation (LDA) in…