7 papers
SyncReward: Human-Aligned Synchronization Reward for Audio-Visual Generation
Kaisi Guan, Ying Ba, Wenjing Wang +4
Recent years have witnessed rapid progress in joint audio--visual generation. However, audio--visual synchronization remains a challenge, as generated speech and sound often tempor…
Loopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding
Haotian Dong, Wenjing Wang, Chen Li +3
Looping videos are essential for practical applications such as web graphics, game development, and social media. However, existing approaches typically fail to generate high-quali…
From Understanding to Erasing: Towards Complete and Stable Video Object Removal
Dingming Liu, Wenjing Wang, Chen Li +2
Video object removal aims to erase target objects while reconstructing visually plausible and temporally coherent content. However, target objects often induce shadows, reflections…
SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
Wenjing Wang, Wenxuan Wang, Songning Lai
While deep learning has significantly advanced accident anticipation, the robustness of these safety-critical systems against real-world perturbations remains a major challenge. We…
Identity as Presence: Towards Appearance and Voice Personalized Joint Audio-Video Generation
Qin Chen, Yingjie Chen, Shilun Lin +9
Recent advances in video synthesis have enabled realistic integration of real individuals, driving demand for identity-aware generation. While emerging methods support joint appear…
Video Generation with Stable Transparency via Shiftable RGB-A Distribution Learner
Haotian Dong, Wenjing Wang, Chen Li +2
Generating RGB-A videos, which include alpha channels for transparency, has wide applications. However, current methods often suffer from low quality due to confusion between RGB a…
Stand-In: A Lightweight and Plug-and-Play Identity Control for Video Generation
Bowen Xue, Zheng-Peng Duan, Qixin Yan +6
Generating high-fidelity human videos that match user-specified identities is important yet challenging in the field of generative AI. Existing methods often rely on an excessive n…