most citedControllable Video Generation: A Survey

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2026

LiveLight: Real-time Streaming Video Relighting with Interactive Control

Yue Ma, Jiangming Wang, Yucheng Wang +8

We present LiveLight, the first diffusion-based framework for real-time streaming video relighting with interactive 3D lighting control. Achieving this is non-trivial, as it requir…

cs.CV2026

EasyVFX: Frequency-Driven Decoupling for Resource-Efficient VFX Generation

Yue Ma, Xu Ye, Qinghe Wang +9

Generating high-fidelity visual effects (VFX) typically demands massive datasets and prohibitive computational power due to the intricate coupling of spatial textures and temporal…

cs.CV2026

CARE-Edit: Condition-Aware Routing of Experts for Contextual Image Editing

Yucheng Wang, Zedong Wang, Yuetong Wu +2

Unified diffusion editors often rely on a fixed, shared backbone for diverse tasks, suffering from task interference and poor adaptation to heterogeneous demands (e.g., local vs gl…

cs.CV2025

MoDiT: Learning Highly Consistent 3D Motion Coefficients with Diffusion Transformer for Talking Head Generation

Yucheng Wang, Dan Xu

Audio-driven talking head generation is critical for applications such as virtual assistants, video games, and films, where natural lip movements are essential. Despite progress in…

cs.GR2025★ 1 cited

Controllable Video Generation: A Survey

Yue Ma, Kunyu Feng, Zhongyuan Hu +19

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video…

cs.CV2025

From One to More: Contextual Part Latents for 3D Generation

Shaocong Dong, Lihe Ding, Xiao Chen +10

Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth da…