HappyHorse Gets Stronger Motion Expressiveness, Higher Generation Consistency, and Enhanced Visual Quality

Alibaba has released HappyHorse 1.1, the upgrade to its video generation model, to deliver enhanced creative quality, controllability, and production efficiency for professional content creators.

HappyHorse1_1_image

Alibaba has released HappyHorse 1.1, the upgrade to its video generation model, to deliver enhanced creative quality, controllability, and production efficiency for professional content creators.

Maintaining character consistency has long been a major bottleneck in AI video generation. To address this, Alibaba has enhanced the model’s ability to interpret and integrate information from multiple reference images. This significantly improves visual consistency between reference images and generated outputs in Reference-to-Video (R2V) tasks, enabling precise visual fidelity for elements such as products, characters, and scenes.

Motion expressiveness has also received a boost. By optimizing motion modeling and temporal consistency, HappyHorse 1.1 delivers smoother, more coherent, and visually striking movement in complex action sequences.

The upgrade also brings improvement in instruction following to better understand user inputs. Visual quality is enhanced for richer visual details and lifelike imagery, while the advanced audio capabilities ensures precise audio-visual synchronization.

Since its release in April, HappyHorse 1.0 has been adopted across various content production sectors, including short-form dramas, e-commerce advertising, brand marketing, and gaming cinematic trailers (CG).

HappyHorse 1.1 is now accessible to individuals and enterprises via its official website happyhorse.com and through an API on on Alibaba’s one-stop, enterprise-grade AI development platform Model Studio.

This article was originally published on Alizila written by Claire Mo.

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