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Hui Fang

12 accepted papers

2026

ACID-Style: An Adaptive Condition Injection Diffusion Model for Arbitrary Style Transfer

AAAI 2026technical

Arbitrary style transfer (AST), a popular AI-powered photo editing function, aims to strike an optimal balance between content and style injection from two images in order to generate a novel high-fidelity stylised image. Recently, diffusion models have been applied to AST due to their high generati

Cited by 0SourcePDFScholar
2025

HHAN: Comprehensive Infectious Disease Source Tracing via Heterogeneous Hypergraph Neural Network

AAAI 2025technical

Infectious diseases have historically had profound effects on global health, economies, and social structures. Effective tracing of infectious diseases is essential not only for immediate public health responses but also for shaping future prevention strategies. Traditional tracing methods often emp…

Cited by 0SourcePDFScholar
2025

Large Language Models Enhanced Personalized Graph Neural Architecture Search in Federated Learning

AAAI 2025technical

Personalized federated learning (PFL) on graphs is an emerging field focusing on the collaborative development of architectures across multiple clients, each with distinct graph data distributions while adhering to strict privacy standards. This area often requires extensive expert intervention in m…

2025

Recoverable Facial Identity Protection via Adaptive Makeup Transfer Adversarial Attacks

AAAI 2025technical

Unauthorised face recognition (FR) systems have posed significant threats to digital identity and privacy protection. To alleviate the risk of compromised identities, recent makeup transfer-based attack methods embed adversarial signals in order to confuse unauthorised FR systems. However, their maj…

2024

CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding Residues

AAAI 2024technical

Accurate identification of protein nucleic acid binding residues poses a significant challenge with important implications for various biological processes and drug design. Many typical computational methods for protein analysis rely on a single model that could ignore either the semantic context of…

2024

HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation

CVPR 2024poster

Event-based semantic segmentation has gained popularity due to its capability to deal with scenarios under high-speed motion and extreme lighting conditions which cannot be addressed by conventional RGB cameras. Since it is hard to annotate event data previous approaches rely on event-to-image recon…

Cited by 5SourcePDFScholar
2024

X4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-Modal Knowledge Transfer

AAAI 2024technical

The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences. However, it remains a challenging task due to the sparsity and lack of texture in point clouds. Moreover, the irregularity of point cloud poses a difficulty in aligning tempo…

2023

Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks

NeurIPS 2023poster

Information diffusion problems, such as the spread of epidemics or rumors, are widespread in society. The inverse problems of graph diffusion, which involve locating the sources and identifying the paths of diffusion based on currently observed diffusion graphs, are crucial to controlling the spread…

Cited by 8SourcePDFScholar
2023

Gradient-Based Graph Attention for Scene Text Image Super-resolution

AAAI 2023technical

Scene text image super-resolution (STISR) in the wild has been shown to be beneficial to support improved vision-based text recognition from low-resolution imagery. An intuitive way to enhance STISR performance is to explore the well-structured and repetitive layout characteristics of text and explo…

2023

Robust Steganography without Embedding Based on Secure Container Synthesis and Iterative Message Recovery

IJCAI 2023poster

Synthesis-based steganography without embedding (SWE) methods transform secret messages to container images synthesised by generative networks, which eliminates distortions of container images and thus can fundamentally resist typical steganalysis tools. However, existing methods suffer from weak me…

Cited by 2SourcePDFScholar
2022

Image Disentanglement Autoencoder for Steganography Without Embedding

CVPR 2022poster

Conventional steganography approaches embed a secret message into a carrier for concealed communication but are prone to attack by recent advanced steganalysis tools. In this paper, we propose Image DisEntanglement Autoencoder for Steganography (IDEAS) as a novel steganography without embedding (SWE…

Cited by 80PDFcodeScholar
2020

Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer

ECCV 2020poster

Photorealistic style transfer is the task of transferring the artistic style of an image onto a content target, producing a result that is plausibly taken with a camera. Recent approaches, based on deep neural networks, produce impressive results but are either too slow to run at practical resolutio…

Cited by 65SourcePDFScholar