https://www.3dart.it/en/free-blob-tracker-plugin-for-after-effects-motion-design-tracking-tool-2/

All output examples from the updated version of my experimental multi-source video player for TouchDesigner, designed for frame-accurate video switching, playback manipulation, and display/render interventions.

Want access to the updated system + a detailed breakdown of exactly how I achieved the continuous motion effect on this piece? You can freely access the system, and the detailed breakdown from my Patreon. 

[Plus, here's a discount code for the community to use at the shop: "AVPLAST", and for memberships: "AVPMEMB". First come, first serve!]

Plus, many more experiments through my Instagram profile.

https://www.3dart.it/en/3d-anatomy-free-in-zbrush-2/

“Ultimate Bony” – A Body Skeleton System Ready to Animate!

We would like to share this interesting resource for all animators: ready-made rigs designed to help you learn the principles of animation, ideal for creating advanced body mechanics animations. Resource by Ugur Ulvi Yetiskin.

https://www.3dart.it/en/free-maya-rigs-and-maya-character-rigs/

Here's the code: https://github.com/meszmate/rebound

Google researchers introduced SHELLS, a new system for reconstructing detailed 3D heads from calibrated multi-view images.

Instead of creating an unstructured scan and then spending minutes or hours fitting a common topology onto it, SHELLS directly predicts an 18K-vertex mesh with consistent topology. Every generated head shares the same vertex layout, which is especially useful for animation, facial tracking and performance capture.

Highlights:

• Reconstructs an 18K-vertex head in 0.08 seconds
• Uses around 2.4 GB of GPU memory during inference
• Approximately 3.5× faster than previous volumetric approaches
• Reduces median registration error by 21–29%
• Produces the same topology across different people and expressions
• Can process facial performances frame by frame while maintaining temporally stable geometry
• Remains usable with as few as two input views
• Trained entirely on synthetic data, but generalizes to real captures

The consistent topology is probably the most practically important part. Corresponding vertices always represent the same facial regions, making the results easier to use for blendshapes, animation retargeting, facial datasets, 3D morphable models and digital-human pipelines.

There are still some limitations. It requires calibrated multi-camera images, so this is not a casual single-image head generator. The current output captures the skin surface beneath hair and clothing rather than reconstructing their outer volume, and the geometry does not include tiny details such as pores or fine wrinkles. Certain extreme tongue expressions can also fail.

The project page currently provides the research paper, but does not list a public codebase or pretrained model release. Humanity has once again invented something extremely fast and then neglected to give everyone the download button.

Source: https://syntec-research.github.io/SHELLS/