Haiyang Zheng (郑海阳)

Open-World Deepfake Attribution via Confidence-Aware Asymmetric Learning

Haiyang Zheng, Nan Pu, Wenjing Li, Teng Long, Nicu Sebe, Zhun Zhong.

AAAI Conference on Artificial Intelligence (AAAI), 2026.

[Paper] [Code]

Mitigating confidence skew and automatically estimating novel forgery types for robust open-world DeepFake attribution.

Generate, Refine, and Encode: Leveraging Synthesized Novel Samples for On-the-Fly Fine-Grained Category Discovery

Xiao Liu, Nan Pu, Haiyang Zheng, Wenjing Li, Nicu Sebe, Zhun Zhong.

International Conference on Computer Vision (ICCV), 2025.

[Paper] [Code]

A diffusion-based framework that synthesizes and refines novel samples to enhance on-the-fly fine-grained category discovery.

Prototypical Hash Encoding for On-the-Fly Fine-Grained Category Discovery

Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, and Zhun Zhong.

Neural Information Processing Systems (NeurIPS), 2024.

[Paper] [Code]

We propose a prototypical hash encoding method to discover fine-grained categories in real-time streams.

Textual Knowledge Matters: Cross-Modality Co-Teaching for Generalized Visual Class Discovery

Haiyang Zheng, Nan Pu, Wenjing Li, Nicu Sebe, and Zhun Zhong.

European Conference on Computer Vision (ECCV), 2024.

[Paper] [Code]

Leveraging textual knowledge to guide visual discovery in generalized settings using a co-teaching framework.

Deep Image Clustering Based on Curriculum Learning and Density Information

Haiyang Zheng, Ruilin Zhang, Hongpeng Wang.

ACM International Conference on Multimedia Retrieval (ICMR), 2024.

[Paper]

Combining curriculum learning strategies with density peaks to improve deep clustering performance.

TDEC: Deep Embedded Image Clustering with Transformer and Distribution Information

Ruilin Zhang, Haiyang Zheng, Hongpeng Wang.

ACM International Conference on Multimedia Retrieval (ICMR), 2023.

[Paper]

A novel Transformer-based framework for deep embedded clustering that exploits distribution information.

📝 Publications