11 citations · 21 across the 18 of their papers we have counts for
10 papers · 1 filter
TinyHistory: Lightweight Video History Embeddings via Two-Stage Context Learning
Lvmin Zhang, Shengqu Cai, Muyang Li +6
History context is central to autoregressive video generation, driving consistency and storytelling for both commercial models and personal use cases. For example, personal users,…
BulletTime: Decoupled Control of Time and Camera Pose for Video Generation
Yiming Wang, Qihang Zhang, Shengqu Cai +7
Emerging video diffusion models achieve high visual fidelity but fundamentally couple scene dynamics with camera motion, limiting their ability to provide precise spatial and tempo…
Mixture of Contexts for Long Video Generation
Shengqu Cai, Ceyuan Yang, Lvmin Zhang +10
Long video generation is fundamentally a long context memory problem: models must retain and retrieve salient events across a long range without collapsing or drifting. However, sc…
Captain Cinema: Towards Short Movie Generation
Junfei Xiao, Ceyuan Yang, Lvmin Zhang +7
We present Captain Cinema, a generation framework for short movie generation. Given a detailed textual description of a movie storyline, our approach firstly generates a sequence o…
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid Motions
Di Chang, Mingdeng Cao, Yichun Shi +7
Editing images with instructions to reflect non-rigid motions, camera viewpoint shifts, object deformations, human articulations, and complex interactions, poses a challenging yet…
CL-Splats: Continual Learning of Gaussian Splatting with Local Optimization
Jan Ackermann, Jonas Kulhanek, Shengqu Cai +5
In dynamic 3D environments, accurately updating scene representations over time is crucial for applications in robotics, mixed reality, and embodied AI. As scenes evolve, efficient…
Frame Context Packing and Drift Prevention in Next-Frame-Prediction Video Diffusion Models
Lvmin Zhang, Shengqu Cai, Muyang Li +2
We present a neural network structure, FramePack, to train next-frame (or next-frame-section) prediction models for video generation. FramePack compresses input frame contexts with…
ReStyle3D: Scene-Level Appearance Transfer with Semantic Correspondences
Liyuan Zhu, Shengqu Cai, Shengyu Huang +3
We introduce ReStyle3D, a novel framework for scene-level appearance transfer from a single style image to a real-world scene represented by multiple views. The method combines exp…
X-Dyna: Expressive Dynamic Human Image Animation
Di Chang, Hongyi Xu, You Xie +12
We introduce X-Dyna, a novel zero-shot, diffusion-based pipeline for animating a single human image using facial expressions and body movements derived from a driving video, that g…
Three-view Focal Length Recovery From Homographies
Yaqing Ding, Viktor Kocur, Zuzana Berger Haladová +4
In this paper, we propose a novel approach for recovering focal lengths from three-view homographies. By examining the consistency of normal vectors between two homographies, we de…