Hybrid Cinematography is a workflow that combines physical capture with generative video reshooting to manage hallucination risk. It uses an editable 3D shot plan and a proxy of the take to evaluate hallucination risk in real time, allowing filmmakers to adjust plans, shoot guided pickups, or accept hallucination. The approach is demonstrated through a mobile AR app for on‑set planning and an offline pipeline for existing video, and a study with experienced filmmakers shows how risk previsualization informs camera decisions and highlights tensions between creative intent and generative hallucination.
By Nhan (Nathan), Tran, Neal Wadhwa, Abe Davis, Stefan Stojanov
arXiv:2603.11421v2 Announce Type: replace
Abstract: Text-driven video generation has democratized film creation, but camera control in cinematic multi-shot scenarios remains a significant block. Impl...
By Songlin Yang, Zhe Wang, Xuyi Yang, Songchun Zhang, Xianghao Kong, Taiyi Wu, Xiaotong Zhao, Ran Zhang, Alan Zhao, Anyi Rao
arXiv:2607. 22959v1 Announce Type: cross Abstract: AI-generated video is increasingly used across marketing, product storytelling, and creative workflows, yet automated; high-precision quality control remains a major constraint to scaling production.
By Aniket Sakpal, Yang Jiang, Rouzbeh Davoudi, Shayan Hassantabar, Mani Najmabadi
arXiv:2604.03315v2 Announce Type: replace
Abstract: Storyboarding is a core skill in visual storytelling for film, animation, and games. However, automating this process requires a system to achieve...
By Bingliang Li, Zhenhong Sun, Jiaming Bian, Yuehao Wu, Yifu Wang, Hongdong Li, Yatao Bian, Huadong Mo, Daoyi Dong
arXiv:2609.24955v1 Announce Type: cross
Abstract: Visual instructions for physical tasks are typically authored in one context and followed in another, requiring users to translate demonstrated tools...
By Muzhe Wu, Zuchen Li, Xu Wang, Anhong Guo
FilmFlow is an agentic framework that transforms natural‑language instructions or reference videos into explicit camera trajectories for dynamic 3D environments. It uses a Director agent that composes high‑level motions from concurrent atomic operations, supported by Interpreter, Scout, and Critic agents for intent extraction, viewpoint selection, and iterative refinement. The authors also introduce CinemaBench, a benchmark of 150 Blender scenes with 750 text‑directed tasks and 60 video‑reference tasks, where FilmFlow outperforms baselines and receives the highest user preference.
By Yiming Zhang, Jiarui Guo, Haojia Wei, Yifei Liu, Yifan Yang, Hongjie Zhang, Xue Yang, Zhihang Zhong
Generative Cinematographer (GenCine) lifts a single image into an editable 3D scene scaffold, allowing artists to jointly author camera paths and foreground motion using local 3D motion handles. The system projects these controls into guidance maps that encode handle positions and colors across frames, enabling a pretrained video model to follow camera-relative, piecewise-rigid motion without physics simulation. Training recovers controls from real videos and synthetic ground-truth geometry, and experiments demonstrate consistent camera-relative motion, improved geometric consistency, and strong controllability across diverse real-world scenes.
By Jiahan Zhang, Chaohao Yang, Namitha Guruprasad, Vivekjyoti Banerjee, Trong-Tung Nguyen, Alan Yuille, Anand Bhattad
The paper introduces a framework for generating multi‑view images of a person within a natural scene, addressing the scarcity of paired multi‑view datasets for human subjects. It evaluates existing diffusion‑based image‑editing models and finds they often hallucinate head‑turn angles, leading to inconsistent backgrounds. To overcome this, the authors propose the Head Scene Rotation Difference (HSRD) metric, which separates camera movement from head pose changes and enables reliable assessment of 3D spatial parallax for constructing high‑quality synthetic datasets.
By Mahir Majid, Young Kyung Kim, Guillermo Sapiro
arXiv:2609.38683v1 Announce Type: cross
Abstract: Cinematic camera motion is a fundamental storytelling tool, defined not only by where the camera is positioned in the scene, but also by how it moves...
By Ziqi Zhou, Yujian Yuan, Laura Sevilla-Lara
Auteur is a language‑driven method that generates human‑centric camera framing for generative video models. It treats shots as framings relative to an actor, encoding shot size, angle, and composition as functions of human pose and motion, and uses a domain‑specific language that converts to standard 6‑DoF camera parameters. A fine‑tuned multimodal large language model acts as a virtual director, mapping natural language descriptions and coarse human motion to sparse DSL keyframes that are interpolated into continuous camera trajectories for video generation.
By Muhammed Burak Kizil, Enes Sanli, Niloy J. Mitra, Xuelin Chen, Erkut Erdem, Aykut Erdem, Duygu Ceylan
CamPilot is a multi‑agent cinematic assistant that combines cinematographic planning with camera‑work control to generate more coherent and aesthetically pleasing movies from text prompts. It learns camera‑work planning from 14,000 professional films using a GRPO‑based learning paradigm, capturing motion patterns, composition principles, and cross‑shot relationships. The system is evaluated with a new benchmark, CamEval, and outperforms existing text‑to‑movie methods in cinematographic control and quality.
By Yang Wu, Stefano Petrangeli, Ishita Dasgupta, Yu Shen
arXiv:2608.29621v1 Announce Type: cross
Abstract: Long-horizon story-driven video generation requires a production agent to coordinate narrative decomposition, state tracking, shot design, prompt con...
By Junxiang Liu, Lin Wang, Haiyu Shi, Hongxu Ma, Xiaoyu Yang, Chunjie Chen, Xiaoxiao Xu, Kaiqiao Zhan, Boao Wang, Shuizhou Shi, Tianyun Zhu, Jie Li, Jiangtong Li