85 citations · 124 across the 13 of their papers we have counts for
13 papers
Integrating Large Pre-trained Models into Multimodal Named Entity Recognition with Evidential Fusion
Weide Liu, Xiaoyang Zhong, Jingwen Hou +3
Multimodal Named Entity Recognition (MNER) is a crucial task for information extraction from social media platforms such as Twitter. Most current methods rely on attention weights…
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…
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…
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…
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)…
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…
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…
Document Visualization using Topic Clouds
Shaohua Li, Tat-Seng Chua
Traditionally a document is visualized by a word cloud. Recently, distributed representation methods for documents have been developed, which map a document to a set of topic embed…
PSDVec: a Toolbox for Incremental and Scalable Word Embedding
Shaohua Li, Jun Zhu, Chunyan Miao
PSDVec is a Python/Perl toolbox that learns word embeddings, i.e. the mapping of words in a natural language to continuous vectors which encode the semantic/syntactic regularities…
Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs)
Shaohua Li, Tat-Seng Chua, Jun Zhu +1
Word embedding maps words into a low-dimensional continuous embedding space by exploiting the local word collocation patterns in a small context window. On the other hand, topic mo…
A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution
Shaohua Li, Jun Zhu, Chunyan Miao
Most existing word embedding methods can be categorized into Neural Embedding Models and Matrix Factorization (MF)-based methods. However some models are opaque to probabilistic in…
On the Equivalence of Factorized Information Criterion Regularization and the Chinese Restaurant Process Prior
Shaohua Li
Factorized Information Criterion (FIC) is a recently developed information criterion, based on which a novel model selection methodology, namely Factorized Asymptotic Bayesian (FAB…
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models
Shaohua Li, Ryohei Fujimaki, Chunyan Miao
Factorial hidden Markov models (FHMMs) are powerful tools of modeling sequential data. Learning FHMMs yields a challenging simultaneous model selection issue, i.e., selecting the n…