Make-It-3D VS MotionDiffuse

Compare Make-It-3D vs MotionDiffuse and see what are their differences.

Make-It-3D

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

MotionDiffuse

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model (by mingyuan-zhang)
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Make-It-3D MotionDiffuse
1 1
1,693 784
- -
6.9 10.0
7 months ago about 1 year ago
Python Python
- GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Make-It-3D

Posts with mentions or reviews of Make-It-3D. 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 Make-It-3D and MotionDiffuse you can also consider the following projects:

DreamCraft3D - [ICLR 2024] Official implementation of DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior

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

NeuralRecon - Code for "NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video", CVPR 2021 oral

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

SegmentAnythingin3D - Segment Anything in 3D with NeRFs (NeurIPS 2023)

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

learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)

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

AvatarPoser - Official Code for ECCV 2022 paper "AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing"

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

unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)