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Junjiang Wu

3 accepted papers

2026

All in One: Unifying Deepfake Detection, Tampering Localization, and Source Tracing with a Robust Landmark-Identity Watermark

CVPR 2026

With the rapid advancement of deepfake technology, malicious face manipulations pose a significant threat to personal privacy and social security. However, existing proactive forensics methods typically treat deepfake detection, tampering localization, and source tracing as independent tasks, lackin

Cited by 0SourcecodeScholar
2025

Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal

AAAI 2025technical

Incomplete multi-view multi-label classification aims to accurately predict labels for each sample in the face of some missing views. Due to its widespread presence in real-world scenarios, it has become an extensively researched topic. In addition to the challenges brought by missing views, it also…

Cited by 0SourcePDFScholar
2024

View-Category Interactive Sharing Transformer for Incomplete Multi-View Multi-Label Learning

CVPR 2024highlight

As a problem often encountered in real-world scenarios multi-view multi-label learning has attracted considerable research attention. However due to oversights in data collection and uncertainties in manual annotation real-world data often suffer from incompleteness. Regrettably most existing multi-…

Cited by 6SourcePDFScholar