Rickko

Researcher at Apple Machine Learning Research

[Midjourney @midjourney]

A technical dive inside our new "Midjourney Scanner"

[Rickko @rickchang85]

@midjourney Would love to join the celebration! I am in SF!

[Rickko @rickchang85]

@xxunhuang Congrats!

[Oncel Tuzel @OncelTuzel]

Great work on 4D representation learning from Anagh’s internship at @Apple, with exciting applications in video-to-4D, 3D tracking, and simulation.

[Anagh Malik @anagh_malik]

📢📢📢 Velox 🚀: Learning Representations of 4D Geometry and Appearance

In our #CVPR2026 paper, we introduce a method for learning a native 4D representation, useful for many downstream tasks, such as video-to-4D, 3D tracking, cloth simulation, and others!

🌐: https://t.co/MCkCMEftoJ
📝: https://t.co/iLKgrprXlO

[Oncel Tuzel @OncelTuzel]

Excited to share that we’ve open-sourced LiTo (ICLR 2026) code + models from @Apple!

Interactive image-to-3D generation from images.

• Apple Silicon demo via MLX
• Full training code

GitHub: https://t.co/wLy5EiHSJW
Paper: https://t.co/Se6k9AWboZ

#Apple #MLX #3D #AI

[Rickko @rickchang85]

Excited to share LiTo: a latent 3D representation for single-stage image-to-3D generation with view-dependent appearance, modeling continuous 3D surfaces as probability densities directly from raw data — no SDF preprocessing required.

[Xiaoming Zhao @xmzhao_]

Most 3D representations capture shape or texture, but rarely both, especially view-dependent effects like reflections.

Check out LiTo: a set of latent tokens that capture both geometry and appearance for high-quality image-to-3D generation.

https://t.co/JaHas1gdNw

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[Rickko @rickchang85]

@bryandada @BigMout15607907 @ofahsueh @CBAJazz https://t.co/sPBpkfDBuj

[Rickko @rickchang85]

@BabyU_Tt @FILMLEE44 @RereKuo @jacksoniscrycry @kasenoshi https://t.co/sPBpkfDBuj