arXiv:2610.29590v1 Announce Type: new
Abstract: Cinematic multi-shot video generation requires both narrative planning and iterative refinement. Existing methods either lack narrative reasoning or re...
By Jingzhe Zhang, Peixuan Zhang, Genying Li, Bing Ma, Shuchen Weng, Si Li, Boxin Shi
arXiv:2606. 07649v1 Announce Type: cross Abstract: Long-form video generation requires systematic narrative planning and visual consistency that current short-clip methods cannot provide.
By Lingxuan Huang, Sizhe He, Hengji Zhou, Liqiang Nie, Lianghao Xia, Chao Huang
arXiv:2609.37407v1 Announce Type: new
Abstract: While recent video foundation models excel at generating high-quality short videos, long-form video generation remains a critical challenge, where a ma...
By Xianghan Wei, Xiaoda Yang, Zhi Wang, An Pan, Daoan Zhang, Huayi Zhang, Yan Zhang, Wei Xu, Zishun Liao, Jianwen Lou
arXiv:2607. 19038v1 Announce Type: cross Abstract: Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-form, multi-scene visual narratives.
By Jialong Zuo, Haotong Zuo, Shiwei Zhang, Xiang Wang, Chen Li, Nong Sang, Changxin Gao, Xiang Bai
arXiv:2607. 06481v1 Announce Type: cross Abstract: We present PACR-Video, a parameter-efficient framework for multi-shot long video extrapolation that preserves recurring entities, scene structure, visual style, and causal progression without full generator fine-tuning.
By Anna C\'ordoba, Adam Puente Tercero, Nerea Angulo Hijo, Mar Linares Tercero, Julia Barrientos, Ainhoa Miranda, Jes\'us Olivera
WanPE is a 397‑B parameter prompt‑enhancement model that learns director‑level cinematic planning from 1.05 M real‑world videos. It generates shot‑level cinematic plans through video‑grounded reverse construction and uses Semantic‑Consistency GRPO (SC‑GRPO) to maintain user intent across shots and time. In evaluations, WanPE improves human preference over raw prompts by up to 50.86 points for 30‑second videos and outperforms commercial offerings for shorter durations.
By Yubo Zhu, Yawen Shao, Ziyun Dai, Zixun Fang, Kai Zhu, Siyang Sun, Haolan Xue, Chuxin Wang, Tingyu Weng, Jingming Luo, Chen Shi, Lianghua Huang, Yufeng Ai, Yuzheng Wang, Wenyuan Zhang, Yu Shang, Yuxiang Bao, Zoubin Bi, Jie Xiao, Jinbo Xing, Jiaxing Zhao, Chongyang Zhong, Hengjian Chen, Chenwei Xie, Akide Liu, Zhehan Kan, Yu Liu, Wei Zhai, Sheng Zhong, Wei Tong
arXiv:2610.00097v1 Announce Type: new
Abstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with con...
By Ting Huang, Biao Wu, Ronghao Chen, Zeyu Zhang, Tengfei Cheng, Qizhen Lan, Huacan Wang, Hao Tang
The paper introduces PEBench, a unified benchmark for evaluating prompt enhancers (PEs) in video generation across text-to-video, image-to-video, and reference-to-video tasks. It contains 1,100 expert-verified cases, 1,005 visual assets, and 35 fine-grained tasks, and employs a fact-extraction and rubric-based assessment framework covering 24 criteria. Evaluation of various PE methods shows a trend toward intent-preserving cinematic planning, with certain methods excelling in coverage or coherence, and human validation confirms that PEBench scores align with expert judgments and downstream video quality.
By Yawen Shao, Yubo Zhu, Ziyun Dai, Zixun Fang, Kai Zhu, Zeyinzi Jiang, Yufeng Ai, Siyang Sun, Haolan Xue, Yu Shang, Yuxiang Bao, Zoubin Bi, Jingming Luo, Jie Xiao, Chaojie Mao, Zhehan Kan, Hongchen Luo, Yu Liu, Sheng Zhong, Wei Tong, Xueyang Fu, Yang Cao, Wei Zhai, Zheng-Jun Zha
arXiv:2608.22725v1 Announce Type: new
Abstract: Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity ha...
By Jiaqi Liu, Maolin Ran, Xiaoyang Lu, Jian Wang, Weiwen Liu, Jianghao Lin, Yong Yu, Weinan Zhang
Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity has become a critical bottleneck. Current agent fra...
arXiv:2606. 13768v1 Announce Type: cross Abstract: Cinematic video depicts multiple subjects acting or interacting at specific moments, captured with deliberate camera movement, and stitched together by shot transitions.
By Sharath Girish, Tsai-Shien Chen, Zhikang Dong, Mukesh Singhal, Hao Chen, Sergey Tulyakov, Aliaksandr Siarohin
Recent advances in video generative models have enabled high-fidelity, temporally coherent video generation. However, these models often struggle to satisfy prompts requiring specialized knowledge, sp...