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RigAnything – Template-Free Autoregressive Rigging for Diverse 3D Assets
https://www.liuisabella.com/RigAnything
RigAnything was developed through a collaboration between UC San Diego, Adobe Research, and Hillbot Inc. It addresses one of 3D animation’s most persistent challenges: automatic rigging.
- Template-Free Autoregressive Rigging. A transformer-based model that sequentially generates skeletons without predefined templates, enabling automatic rigging across diverse 3D assets through probabilistic joint prediction and skinning weight assignment.
- Support Arbitrary Input Pose. Generates high-quality skeletons for shapes in any pose through online joint pose augmentation during training, eliminating the common rest-pose requirement of existing methods and enabling broader real-world applications.
- Fast Rigging Speed. Achieves 20x faster performance than existing template-based methods, completing rigging in under 2 seconds per shape.
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Skywork SkyReels – All-in-one open source AI video creation based on Hynyuan
https://github.com/SkyworkAI/SkyReels-V1
All-in-one AI platform for video creation, including voiceover, lipsync, SFX, and editing. One click turn text to video & image to video. Turns idea into stunning video in minutes. Check Pricing Details. Start For Free. All-In-One Platform.
SkyReels-V1 is purpose-built for AI short video production based on Hynyuan. It achieves cinematic-grade micro-expression performances with 33 nuanced facial expressions and 400+ natural body movements that can be freely combined. The model integrates film-quality lighting aesthetics, generating visually stunning compositions and textures through text-to-video or image-to-video conversion – outperforming all existing open-source models across key metrics.
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Shanhai based StepFun – Open source Step-Video-T2V
https://huggingface.co/stepfun-ai/stepvideo-t2v
The model generates videos up to 204 frames, using a high-compression Video-VAE (16×16 spatial, 8x temporal). It processes English and Chinese prompts via bilingual text encoders. A 3D full-attention DiT, trained with Flow Matching, denoises latent frames conditioned on text and timesteps. A video-based DPO further reduces artifacts, enhancing realism and smoothness.
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InvokeAI Got a Copyright for an Image Made Entirely With AI. Here’s How
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