1 citations · 1 across the 12 of their papers we have counts for
25 papers
FilmWeaver: Weaving Consistent Multi-Shot Videos with Cache-Guided Autoregressive Diffusion
Xiangyang Luo, Qingyu Li, Xiaokun Liu +7
Current video generation models perform well at single-shot synthesis but struggle with multi-shot videos, facing critical challenges in maintaining character and background consis…
PatchVSR: Breaking Video Diffusion Resolution Limits with Patch-wise Video Super-Resolution
Shian Du, Menghan Xia, Chang Liu +5
Pre-trained video generation models hold great potential for generative video super-resolution (VSR). However, adapting them for full-size VSR, as most existing methods do, suffers…
FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generation
Kaiyi Huang, Yukun Huang, Xintao Wang +6
AI-driven content creation has shown potential in film production. However, existing film generation systems struggle to implement cinematic principles and thus fail to generate pr…
FullDiT2: Efficient In-Context Conditioning for Video Diffusion Transformers
Xuanhua He, Quande Liu, Zixuan Ye +7
Fine-grained and efficient controllability on video diffusion transformers has raised increasing desires for the applicability. Recently, In-context Conditioning emerged as a power…
UNIC: Unified In-Context Video Editing
Zixuan Ye, Xuanhua He, Quande Liu +7
Recent advances in text-to-video generation have sparked interest in generative video editing tasks. Previous methods often rely on task-specific architectures (e.g., additional ad…
CamCloneMaster: Enabling Reference-based Camera Control for Video Generation
Yawen Luo, Jianhong Bai, Xiaoyu Shi +6
Camera control is crucial for generating expressive and cinematic videos. Existing methods rely on explicit sequences of camera parameters as control conditions, which can be cumbe…