arXiv Computer Vision
CineEvolve: An Agentic Self-Evolution Framework for Cinematic Multi-Shot Video Generation
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CineForge: Self-Improving Agents for Long-Horizon Video Generation
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...
arXiv Computer Vision
Aug 25
ShotVerse: Advancing Cinematic Camera Control for Text-Driven Multi-Shot Video Creation
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...
arXiv Computer Vision
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MVAgent: Multi-Agent Video Generation via Consistent Condition Construction and Shot-Level Policy Optimization
MVAgent is a multi‑agent pipeline for multi‑shot video generation that ensures consistent character appearance, stable spatial layout, and continuous character state across shots. The system uses typed conditioning inputs: a Spatial Grounding agent samples camera views, an Observer records shot endings into a continuity memory, a Transition agent builds action and spatial references for subsequent shots, and an Orchestrator composes these inputs into generator requests. Trained with agentic reinforcement learning (Trunk‑GDPO) while keeping the generator and judges frozen, MVAgent achieves the highest cross‑shot consistency and narrative‑planning quality on ViMax‑Bench and is preferred over the strongest agentic baseline in human evaluation.
arXiv Computer Vision
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CamPilot: A Multi-Agent Cinematic Assistant for Camera-Controlled Movie Generation
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.
arXiv AI
Oct 1
Unveiling the Value of Motion for Cinematic Camera Trajectories
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...
arXiv AI
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ViMax: Agentic Video Generation
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.