22. Mai 2023 Johannes Wolters

Lukas Kapp, Ludwigsburg: I’m thrilled to present my latest Creature TD reel!


Lukas Kapp wrote:

I’m thrilled to present my latest Creature TD reel!

Over the past few years, I’ve had the privilege of bringing to life a number of extraordinary creatures in collaboration with some truly awesome people. One project I was honored to be a part of even won this year’s coveted VES Award for its stunning visual effects, a feat that still amazes me. I’m deeply grateful to have had the opportunity to contribute to its success.

As I eagerly embark on the next chapter of my career, I’m particularly interested in the opportunities available in Vancouver, thanks to my open work permit. I’m eager to take on new challenges, expand my horizons, and continue to grow in my craft. If you know of any interesting projects or job openings, I’d love to hear from you.

Finally, if you have a few moments to spare, I invite you to explore my demo reel. Enjoy and thank you for your support!

Creature TD Reel 2023 from Lukas Kapp on Vimeo.

00:02 – ‘A Calling. From the Desert. To the Sea’ (Filmakademie Baden-Württemberg, 2022)
– 21st VES Award for ‚Outstanding Visual Effects in a Student Project‘
– all rigging, muscle/fat/skin sim setup and shot work, shot sculpting (Maya, ZivaVFX)

00:40 – Fleshy Eyes System of Ghoul
– sculpting of all visible FACS shapes, all rigging, animation

00:55 – ‚The Nevers‘ Season 1 | Part 2 (VFX Episodic, Accenture Song VFX, 2022)
– scripted full body rigging incl. mechanics and cables of this dog/machine hybrid (except heart/mechanics inside ribcage) (Maya)
– creating a procedural rigging tool in Python for the dog
– muscle/fat sim setup incl. leather and metal parts (ZivaVFX)
– create tool for this setup in Python to automate shot work for colleagues

01:16 – Modular Rig Tool (Maya, Python)
– scripted modular rig system in Python that I’m using for all my rigs
– joints and locators as input data
– each rig module is its own blackbox that gets connected via in- and outputs
– control shapes saved as a json template that gets applied in the end

01:34 – Inverse Rig Mapping (Research Project, Filmakademie Baden-Württemberg, 2023)
– map skeletal animation e.g. mocap data back to rigs using Machine Learning (PyTorch, Python)
– based on paper “Learning an Inverse Rig Mapping for Character Animation“ by Daniel Holden
– learn dependency between rig control attributes and joint attributes
– use that trained model to predict rig control values based on the skeletal animation data

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