DeepMind Blog
Jan 13
Veo 3.1 Ingredients to Video: More consistency, creativity and control
Our latest Veo update generates lively, dynamic clips that feel natural and engaging — and supports vertical video generation.
Fuel your creativity with new generative media models and tools
Introducing Veo 3 and Imagen 4, and a new tool for filmmaking called Flow.
Related stories
Hugging Face Trending Papers
Jul 14
DiTailed: Ensuring Visual Object Consistency in Text-Image-to-Image Flow Matching Models
Despite remarkable progress in text-guided image editing, generative models frequently fail to preserve visual object consistency, defined as the preservation of a subject's key attributes throughout the editing process. We address this limitation through three contributions.
DeepMind Blog
Oct 25, 2025
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.
arXiv AI
Aug 11
Generative Models: Principles, Architectures, and Applications
arXiv:2608. 08101v1 Announce Type: new Abstract: Generative AI has emerged as one of the most transformative forces in modern artificial intelligence, reshaping how we create, imagine, and interact with digital content.
DeepMind Blog
Oct 23, 2025
Introducing Veo 3.1 and advanced creative capabilities
We’re rolling out significant updates to Veo that give people even more creative control.
arXiv Machine Learning
Jul 27
Unboxing Diffusion Models for the Arts: Interactive Model Bending and Practice-Based Explainability
arXiv:2607.
arXiv Machine Learning
23h ago
From Diffusion to Flow: Efficient Motion Generation in MotionGPT3
arXiv:2603. 26747v3 Announce Type: replace-cross Abstract: Recent text-driven motion generation methods span both discrete token-based approaches and continuous-latent formulations.
arXiv Machine Learning
Jun 26
DanceOPD: On-Policy Generative Field Distillation
arXiv:2606. 27377v1 Announce Type: cross Abstract: Modern image generation demands a single model that unifies diverse capabilities, including text-to-image (T2I), local editing, and global editing.
arXiv AI
Jul 28
FilmBench: A Film-Grade Benchmark for Cinematic Video Generation
arXiv:2607. 24241v1 Announce Type: cross Abstract: Progress in video generation keeps narrowing the visual gap between AI-generated and professionally produced footage, yet most benchmarks still draw prompts from web sources or LLM templates and score them with untrained, generic multimodal models.
OpenAI Blog
Mar 25, 2025
Introducing 4o Image Generation
At OpenAI, we have long believed image generation should be a primary capability of our language models. That’s why we’ve built our most advanced image generator yet into GPT‑4o.
Hugging Face Trending Papers
Jul 27
FilmBench: A Film-Grade Benchmark for Cinematic Video Generation
Progress in video generation keeps narrowing the visual gap between AI-generated and professionally produced footage, yet most benchmarks still draw prompts from web sources or LLM templates and score them with untrained, generic multimodal models. More fundamentally, their evaluation taxonomies remain rudimentary (overall visual quality, coarse text alignment and temporal smoothness) rather than the professional Cinematic Language criteria by which films are actually made and judged, so they assess basic video plausibility rather than film-grade craft.
Hugging Face Trending Papers
Jun 4
ShotCrop$^3$: Cropping Human-Centric Images into Cinematic Triple-Shot Compositions
Prior work on aesthetic composition typically produces a single aesthetically pleasing crop, overlooking the narrative value of composing multiple shots from one scene. In practice, multi-shot composition is critical for downstream creative workflows: commercial posters often require multiple crops with different emphases (e.