add-thin VS MotionDiffuse

Compare add-thin vs MotionDiffuse and see what are their differences.

add-thin

This is the reference implementation of our NeurIPS 2023 paper "Add and Thin: Diffusion for Temporal Point Processes" (by davecasp)

MotionDiffuse

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model (by mingyuan-zhang)
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add-thin MotionDiffuse
1 1
12 784
- -
5.5 10.0
2 months ago over 1 year ago
Python Python
MIT License GNU General Public License v3.0 or later
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add-thin

Posts with mentions or reviews of add-thin. We have used some of these posts to build our list of alternatives and similar projects.

MotionDiffuse

Posts with mentions or reviews of MotionDiffuse. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing add-thin and MotionDiffuse you can also consider the following projects:

prolificdreamer - Official code of ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation (NeurIPS 2023 Spotlight)

StableVideo - [ICCV 2023] StableVideo: Text-driven Consistency-aware Diffusion Video Editing

text-to-motion - Official implementation for "Generating Diverse and Natural 3D Human Motions from Texts (CVPR2022)."

text2room - Text2Room generates textured 3D meshes from a given text prompt using 2D text-to-image models (ICCV2023).

AvatarCLIP - [SIGGRAPH 2022 Journal Track] AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

Make-It-3D - [ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior

MotionGPT - [NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs