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Jiazhi Guan

6 accepted papers

2025

AudCast: Audio-Driven Human Video Generation by Cascaded Diffusion Transformers

CVPR 2025poster

Despite the recent progress of audio-driven video generation, existing methods mostly focus on driving facial movements, leading to non-coherent head and body dynamics. Moving forward, it is desirable yet challenging to generate holistic human videos with both accurate lip-sync and delicate co-speec…

Cited by 0SourcePDFScholar
2025

GestureHYDRA: Semantic Co-speech Gesture Synthesis via Hybrid Modality Diffusion Transformer and Cascaded-Synchronized Retrieval-Augmented Generation

ICCV 2025poster

While increasing attention has been paid to co-speech gesture synthesis, most previous works neglect to investigate hand gestures with explicit and essential semantics. In this paper, we study co-speech gesture generation with an emphasis on specific hand gesture activation, which can deliver more i…

Cited by 0SourcePDFScholar
2024

Adversarial Robust Safeguard for Evading Deep Facial Manipulation

AAAI 2024technical

The non-consensual exploitation of facial manipulation has emerged as a pressing societal concern. In tandem with the identification of such fake content, recent research endeavors have advocated countering manipulation techniques through proactive interventions, specifically the incorporation of ad…

Cited by 3SourcePDFScholar
2024

ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling

NeurIPS 2024poster

Although significant progress has been made in human video generation, most previous studies focus on either human facial animation or full-body animation, which cannot be directly applied to produce realistic conversational human videos with frequent hand gestures and various facial movements simul…

Cited by 4SourcePDFScholar
2023

StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-Based Generator

CVPR 2023poster

Despite recent advances in syncing lip movements with any audio waves, current methods still struggle to balance generation quality and the model's generalization ability. Previous studies either require long-term data for training or produce a similar movement pattern on all subjects with low quali…

Cited by 71SourcePDFScholar
2022

Delving into Sequential Patches for Deepfake Detection

NeurIPS 2022accept

Recent advances in face forgery techniques produce nearly visually untraceable deepfake videos, which could be leveraged with malicious intentions. As a result, researchers have been devoted to deepfake detection. Previous studies have identified the importance of local low-level cues and temporal i…

Cited by 66SourcePDFScholar