4 papers · 1 filter
Open-World Deepfake Attribution via Confidence-Aware Asymmetric Learning
Haiyang Zheng, Nan Pu, Wenjing Li +3
The proliferation of synthetic facial imagery has intensified the need for robust Open-World DeepFake Attribution (OW-DFA), which aims to attribute both known and unknown forgeries…
Generalized Fine-Grained Category Discovery with Multi-Granularity Conceptual Experts
Haiyang Zheng, Nan Pu, Wenjing Li +2
Generalized Category Discovery (GCD) is an open-world problem that clusters unlabeled data by leveraging knowledge from partially labeled categories. A key challenge is that unlabe…
Beyond Artificial Misalignment: Detecting and Grounding Semantic-Coordinated Multimodal Manipulations
Jinjie Shen, Yaxiong Wang, Lechao Cheng +2
The detection and grounding of manipulated content in multimodal data has emerged as a critical challenge in media forensics. While existing benchmarks demonstrate technical progre…
Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery
Xiao Liu, Nan Pu, Haiyang Zheng +3
In this paper, we investigate a practical yet challenging task: On-the-fly Category Discovery (OCD). This task focuses on the online identification of newly arriving stream data th…