Ziva VFX 2.1 Has Been Released

The updated version of the plug-in replaces Discrete Collision Detection with Continuous Collision Detection, adds the Curvature stiffness attribute to the zMaterial node, and supports Maya 2023.

Unity has released Ziva VFX 2.1, a new and improved version of the soft-tissue simulation plug-in for Maya developed by Ziva Dynamics and acquired by Unity last year alongside its developer. The update features several new features and enhancements, focusing primarily on improvements to simulation performance.

The new version's most notable enhancement is that Discrete Collision Detection has been replaced by Continuous Collision Detection, which interpolates the past and current position of vertices to find contact points, improving the simulation quality. According to the devs, this change allows one to significantly reduce the number of substeps while retaining the same visual accuracy.

On top of that, the update adds the Curvature stiffness attribute, an attribute that makes the tissue more resistant to bending, to the zMaterial node, enabling one to tweak and customize the resistance of tissues.

Additionally, the update brings a new damping attribute to the zAttachment node, which connects layers of tissue in simulations, adding the ability to decrease the presence of oscillatory/unstable behavior in attachments.

The update also features:

  • Maya 2023 is now supported.
  • -logFileQuery and -logFile flags are added to the Ziva commands.
    The former flag returns the current log file path and the latter flag allows the user to set a custom log file.
  • zBone/zTissue/zCloth enable attribute is now connectable.
  • Bug fixes

See the full list of changes here and purchase Ziva VFX for Maya over here. Also, don't forget to join our 80 Level Talent platformour Reddit page, and our Telegram channel, follow us on Instagram and Twitter, where we share breakdowns, the latest news, awesome artworks, and more.

Join discussion

Comments 0

    You might also like

    We need your consent

    We use cookies on this website to make your browsing experience better. By using the site you agree to our use of cookies.Learn more