CoaG introduces a minimal geometric interface— a ground plane grid and a single cylinder per person—to control the placement and movement of people and the camera in generated videos. Users draw the grid, position cylinders, and animate them over 81 frames; the model then renders a photorealistic video that follows these layouts and camera paths, with appearance guided by a text prompt and a background image. To train the system, the authors automatically generate 2,000 captioned clips, reconstruct geometry from each clip, and fine‑tune a LoRA on Wan2.2‑Fun‑Control, enabling the model to respect user‑drawn layouts and camera motions on unseen clips.
By Zhangsihao Yang, Mengyi Shan
We ask how little geometry a person has to draw to control both where people stand and where the camera moves in a generated video. Our answer is a ground plane and one cylinder per person. A user dra...
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
arXiv:2610.28632v1 Announce Type: cross
Abstract: Video generation models can now depict remarkably realistic motion. Yet it is unclear how to use this motion beyond pixels: to animate a specific 3D...
By Noam Rotstein, Yoad Tewel, Chen Tessler, Haggai Maron, Gal Chechik, Or Litany, Yoni Kasten, Yuval Atzmon
MUGEN is a large‑scale real‑world dataset of over 1,300 hours of 4K panoramic videos with rich semantic and geometric annotations, designed to support interactive 360° world exploration. Wan360 is a camera‑controllable panoramic video generation model built on MUGEN, featuring ERP‑aware components (periodic longitude RoPE, ERP‑aware padding, random roll yaw) and a panoramic Plücker embedding for camera motion. Together, they address gaps in data and model support for immersive, temporally coherent 360° video generation along user‑specified camera trajectories.
By Jiaming Tan, Zhen Li, Shuwei Shi, Minggui Teng, Siqi Yang, Yuwei Wu, Bo Zheng, Chuanhao Li, Kaipeng Zhang
arXiv:2608. 20335v1 Announce Type: new Abstract: We present 4DAnyone, a framework for reconstructing 4D humans from an uncalibrated monocular video by generating reconstruction-grade multiview-consistent videos and lifting them into 4D Gaussian Splatting (4DGS).
By Yudong Jin, Tao Xie, Qihang Zhang, Zehong Shen, Zhen Xu, Yujun Shen, Hujun Bao, Xiaowei Zhou, Yinghao Xu