collaborators

6 papers

cs.CV2026

HECTOR: Hybrid Editable Compositional Object References for Video Generation

Guofeng Zhang, Angtian Wang, Jacob Zhiyuan Fang +4

Real-world videos naturally portray complex interactions among distinct physical objects, effectively forming dynamic compositions of visual elements. However, most current video g…

cs.CV2025

StoryMem: Multi-shot Long Video Storytelling with Memory

Kaiwen Zhang, Liming Jiang, Angtian Wang +6

Visual storytelling requires generating multi-shot videos with cinematic quality and long-range consistency. Inspired by human memory, we propose StoryMem, a paradigm that reformul…

cs.CV2025

TGT: Text-Grounded Trajectories for Locally Controlled Video Generation

Guofeng Zhang, Angtian Wang, Jacob Zhiyuan Fang +8

Text-to-video generation has advanced rapidly in visual fidelity, whereas standard methods still have limited ability to control the subject composition of generated scenes. Prior…

cs.CV2025

MAGREF: Masked Guidance for Any-Reference Video Generation with Subject Disentanglement

Yufan Deng, Yuanyang Yin, Xun Guo +8

We tackle the task of any-reference video generation, which aims to synthesize videos conditioned on arbitrary types and combinations of reference subjects, together with textual p…

cs.CV2025

ATI: Any Trajectory Instruction for Controllable Video Generation

Angtian Wang, Haibin Huang, Jacob Zhiyuan Fang +2

We propose a unified framework for motion control in video generation that seamlessly integrates camera movement, object-level translation, and fine-grained local motion using traj…

cs.CV2025

CINEMA: Coherent Multi-Subject Video Generation via MLLM-Based Guidance

Yufan Deng, Xun Guo, Yizhi Wang +7

Video generation has witnessed remarkable progress with the advent of deep generative models, particularly diffusion models. While existing methods excel in generating high-quality…