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20212026
most citedLearning to Disentangle GAN Fingerprint for Fake Image Attribution

10 citations · 12 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

TryOnCrafter: Unleashing Camera Trajectories for Realistic Video Virtual Try-on via a Renderable 4D Try-on Proxy

Hao Sun, Hao Yan, Mengting Chen +7

While Video Virtual Try-on (VVT) has achieved remarkable progress in synthesizing realistic garment overlays on dynamic subjects, existing paradigms remains fundamentally constrain…

cs.CV2026

Fleet: Few Shots Lead Effective AI-generated Image Detection

Jiaan Wang, Sirui Liu, Yu Li +3

AI-generated image (AIGI) detection is undergoing a critical transition from laboratory benchmarks to open-world adversarial defense. The prevalent paradigm focuses on finding stat…

cs.CV2025

Beyond Semantic Features: Pixel-level Mapping for Generalized AI-Generated Image Detection

Chenming Zhou, Jiaan Wang, Yu Li +3

The rapid evolution of generative technologies necessitates reliable methods for detecting AI-generated images. A critical limitation of current detectors is their failure to gener…

cs.CV2025

Attend to Not Attended: Structure-then-Detail Token Merging for Post-training DiT Acceleration

Haipeng Fang, Sheng Tang, Juan Cao +3

Diffusion transformers have shown exceptional performance in visual generation but incur high computational costs. Token reduction techniques that compress models by sharing the de…

cs.CV2024

DragEntity: Trajectory Guided Video Generation using Entity and Positional Relationships

Zhang Wan, Sheng Tang, Jiawei Wei +2

In recent years, diffusion models have achieved tremendous success in the field of video generation, with controllable video generation receiving significant attention. However, ex…

cs.CV2023★ 1 cited

Topology-preserving Adversarial Training for Alleviating Natural Accuracy Degradation

Xiaoyue Mi, Fan Tang, Yepeng Weng +5

Despite the effectiveness in improving the robustness of neural networks, adversarial training has suffered from the natural accuracy degradation problem, i.e., accuracy on natural…

cs.CV2023★ 1 cited

Dance Your Latents: Consistent Dance Generation through Spatial-temporal Subspace Attention Guided by Motion Flow

Haipeng Fang, Zhihao Sun, Ziyao Huang +3

The advancement of generative AI has extended to the realm of Human Dance Generation, demonstrating superior generative capacities. However, current methods still exhibit deficienc…

cs.CV2023

Progressive Open Space Expansion for Open-Set Model Attribution

Tianyun Yang, Danding Wang, Fan Tang +3

Despite the remarkable progress in generative technology, the Janus-faced issues of intellectual property protection and malicious content supervision have arisen. Efforts have bee…

cs.CV2021★ 10 cited

Learning to Disentangle GAN Fingerprint for Fake Image Attribution

Tianyun Yang, Juan Cao, Qiang Sheng +4

Rapid pace of generative models has brought about new threats to visual forensics such as malicious personation and digital copyright infringement, which promotes works on fake ima…