prolificdreamer
VideoLoop3D
prolificdreamer | VideoLoop3D | |
---|---|---|
5 | 1 | |
1,387 | 56 | |
3.0% | - | |
4.5 | 4.6 | |
6 months ago | 3 months ago | |
Python | Python | |
Apache License 2.0 | - |
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prolificdreamer
- ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation
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Magic123: One Image to High-Quality 3D Object Generation
Interesting work! But given the time and complexity of the generation, I think VSD-loss based implementations have higher fidelity. See https://github.com/thu-ml/prolificdreamer or https://github.com/threestudio-project/threestudio/tree/main...
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[D] NeRF, LeRF, Prolific Dreamer, Neuralangelo, and a lot of other cool NeRF research
[Code] https://github.com/thu-ml/prolificdreamer
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Is it possible for me to approximate a depth map from a generated image and make a 3D model?
Personally, I'm waiting for code to drop for this one: https://github.com/thu-ml/prolificdreamer
VideoLoop3D
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[D] NeRF, LeRF, Prolific Dreamer, Neuralangelo, and a lot of other cool NeRF research
[Code] https://github.com/limacv/VideoLoop3D
What are some alternatives?
hyperreel - Code release for HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Sampling
ms-nerf - Multi-Space Neural Radiance Fields(CVPR 2023)
stable-diffusion-howto - Run Stable Diffusion on your M1 Mac’s GPU (Intel and non-Apple PCs are also supported)
Neural-Scene-Flow-Fields - PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes"
instruct-pix2pix
MixNeRF - [CVPR2023] MixNeRF: Modeling a Ray with Mixture Density for Novel View Synthesis from Sparse Inputs
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
Sin3DGen
threestudio - A unified framework for 3D content generation.
HiFA
BungeeNeRF - [ECCV22] BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Rendering
f2-nerf - Fast neural radiance field training with free camera trajectories