10 citations · 11 across the 5 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
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…
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…
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…