Hehe Fan

About Hehe Fan

Hehe Fan, With an exceptional h-index of 19 and a recent h-index of 18 (since 2020), a distinguished researcher at National University of Singapore, specializes in the field of Deep learning, Computer vision, Multimedia, AI for science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Clustering for Protein Representation Learning

DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding

ProtChatGPT: Towards Understanding Proteins with Large Language Models

HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splatting

Hand-Centric Motion Refinement for 3D Hand-Object Interaction via Hierarchical Spatial-Temporal Modeling

Uncovering What, Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly

DR-FER: Discriminative and Robust Representation Learning for Facial Expression Recognition

Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering

Hehe Fan Information

University

Position

___

Citations(all)

1880

Citations(since 2020)

1819

Cited By

553

hIndex(all)

19

hIndex(since 2020)

18

i10Index(all)

23

i10Index(since 2020)

22

Email

University Profile Page

Google Scholar

Hehe Fan Skills & Research Interests

Deep learning

Computer vision

Multimedia

AI for science

Top articles of Hehe Fan

Clustering for Protein Representation Learning

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

2024/3/30

DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding

2024/2/20

ProtChatGPT: Towards Understanding Proteins with Large Language Models

arXiv preprint arXiv:2402.09649

2024/2/15

HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splatting

arXiv preprint arXiv:2402.06149

2024/2/9

Hand-Centric Motion Refinement for 3D Hand-Object Interaction via Hierarchical Spatial-Temporal Modeling

2024/1/29

Hehe Fan
Hehe Fan

H-Index: 10

Uncovering What, Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly

arXiv preprint arXiv:2405.00181

2024/4/30

DR-FER: Discriminative and Robust Representation Learning for Facial Expression Recognition

IEEE Transactions on Multimedia

2023/12/28

Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering

IEEE Transactions on Multimedia

2023/12/20

Building Category Graphs Representation with Spatial and Temporal Attention for Visual Navigation

ACM Transactions on Multimedia Computing, Communications and Applications

2023/12/6

A Reliable Representation with Bidirectional Transition Model for Visual Reinforcement Learning Generalization

arXiv preprint arXiv:2312.01915

2023/12/4

Prior-Free Continual Learning with Unlabeled Data in the Wild

arXiv preprint arXiv:2310.10417

2023/10/16

DPMix: Mixture of Depth and Point Cloud Video Experts for 4D Action Segmentation

arXiv preprint arXiv:2307.16803

2023/7/31

A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023

First Place in CVPR 2023 UDA Action Recognition Challenge

2023/7/13

Text to Point Cloud Localization with Relation-Enhanced Transformer

Proceedings of the AAAI Conference on Artificial Intelligence

2023/6/26

Hehe Fan
Hehe Fan

H-Index: 10

Mohan Kankanhalli
Mohan Kankanhalli

H-Index: 38

SEFormer: Structure Embedding Transformer for 3D Object Detection

Proceedings of the AAAI Conference on Artificial Intelligence

2023/6/26

STPrivacy: Spatio-temporal privacy-preserving action recognition

2023

Point Contrastive Prediction with Semantic Clustering for Self-Supervised Learning on Point Cloud Videos

2023

Masked Spatio-Temporal Structure Prediction for Self-supervised Learning on Point Cloud Videos

2023

PointListNet: Deep Learning on 3D Point Lists

2023

Continuous-Discrete Convolution for Geometry-Sequence Modeling in Proteins

2023

See List of Professors in Hehe Fan University(National University of Singapore)

Co-Authors

academic-engine