Veo 3.1 Ingredients to Video: More consistency, creativity and control

Introducing Veo 3.1 and advanced creative capabilities

We’re rolling out significant updates to Veo that give people even more creative control.

Fuel your creativity with new generative media models and tools

Introducing Veo 3 and Imagen 4, and a new tool for filmmaking called Flow.

Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation

Vidu S2 is a system that includes Vidu S2-Avatar, a real‑time interactive digital‑character model, and Vidu S2-Editing, a real‑time video editing model. It enables real‑time 720p video generation with dynamic references and improved instruction following, such as dancing, and allows real‑time editing of video streams for style rendering, clothing replacement, character replacement, and background replacement. Experiments show Vidu S2 outperforms all baselines, and a playable online demo is available at https://vidu.com/vidu-stream.

Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation

arXiv:2607.26694v3 Announce Type: replace Abstract: We present Visko Orbis 1.0, a Live Model for real-time, interactive long video generation. Users can change the prompt at any moment during generat...

TokenDial: Continuous Attribute Control for Text-to-Video Generation in Visual Dial Space

TokenDial introduces a Visual Dial Space (V+) where the channel dimension of visual patch tokens in video diffusion transformers acts as a semantic control space. By learning additive directions in V+, the framework enables continuous slider-style edits for appearance and motion attributes without altering the pretrained generator. The method demonstrates improved controllability and content preservation compared to prior video editing techniques.

Exo2EgoSyn: Unlocking Foundation Video Generation Models for Exocentric-to-Egocentric Video Synthesis

arXiv:2511.20186v2 Announce Type: replace Abstract: Foundation video generation models such as WAN 2.2 exhibit strong text- and image-conditioned synthesis abilities but remain constrained to the sam...

Loopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding

arXiv:2608.23090v1 Announce Type: new Abstract: Looping videos are essential for practical applications such as web graphics, game development, and social media. However, existing approaches typicall...

FineVideo: behind the scenes

WanPE: Towards Cinematic Prompt Enhancement for Modern Text-to-Video Generation

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.

Behind “ANCESTRA”: combining Veo with live-action filmmaking

We partnered with Darren Aronofsky, Eliza McNitt and a team of more than 200 people to make a film using Veo and live-action filmmaking.

LooseControlVideo: Directorial Video Control using Spatial Blocking

Precise 3D spatial orchestration in text-to-video generation remains a significant challenge, particularly for multi-object scenes where semantic layout and temporal dynamics are often entangled. While existing depth-conditioned models achieve good structural fidelity, they necessitate dense, frame-accurate guidance that is labor-intensive to author for dynamic events involving deformable objects.

Motion Attribution for Video Generation

arXiv:2601. 08828v2 Announce Type: replace-cross Abstract: Despite the rapid progress of video generation models, the role of data in influencing motion is poorly understood.