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Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Text Outperforms previous SotA motion synthesis methods across the board proj: abs:

38,401 Aufrufe • vor 2 Jahren •via X (Twitter)

6 Kommentare

Profilbild von Pseudonym 🦅
Pseudonym 🦅vor 2 Jahren

Looks like we have all the pieces now to have a LLM assemble a 3d universe. Motion, physics, models, textures, voice, and endless content all from natural language. Surely someone is working on this? If not someone mail me large crates of cash 😂

Profilbild von kache
kachevor 2 Jahren

weits

Profilbild von Chef Wang
Chef Wangvor 2 Jahren

Astonishing

Profilbild von Emma Catnip
Emma Catnipvor 2 Jahren

✨👀✨

Profilbild von Sourav Kumar Bose
Sourav Kumar Bosevor 2 Jahren

🤯 AI-generated animated films are almost here!

Profilbild von Adrian Perdjon
Adrian Perdjonvor 1 Jahr

RigPlay dataset might be perfect for your development. Learn more at [email protected]

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Alibaba presents MIMO Controllable Character Video Synthesis with Spatial Decomposed Modeling Character video synthesis aims to produce realistic videos of animatable characters within lifelike scenes. As a fundamental problem in the computer vision and graphics community, 3D works typically require multi-view captures for per-case training, which severely limits their applicability of modeling arbitrary characters in a short time. Recent 2D methods break this limitation via pre-trained diffusion models, but they struggle for pose generality and scene interaction. To this end, we propose MIMO, a novel framework which can not only synthesize character videos with controllable attributes (i.e., character, motion and scene) provided by simple user inputs, but also simultaneously achieve advanced scalability to arbitrary characters, generality to novel 3D motions, and applicability to interactive real-world scenes in a unified framework. The core idea is to encode the 2D video to compact spatial codes, considering the inherent 3D nature of video occurrence. Concretely, we lift the 2D frame pixels into 3D using monocular depth estimators, and decompose the video clip to three spatial components (i.e., main human, underlying scene, and floating occlusion) in hierarchical layers based on the 3D depth. These components are further encoded to canonical identity code, structured motion code and full scene code, which are utilized as control signals of synthesis process. The design of spatial decomposed modeling enables flexible user control, complex motion expression, as well as 3D-aware synthesis for scene interactions. Experimental results demonstrate effectiveness and robustness of the proposed method.

AK

149,079 Aufrufe • vor 1 Jahr