Deep Learning experiments
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Updated
Apr 2, 2023 - Python
Deep Learning experiments
3D Human Generation With Mesh From 2D Images
[CVPR2024] DiffusionGAN3D: Boosting Text-guided 3D Generation and Domain Adaptation by Combining 3D GANs and Diffusion Priors.
Custom rendered 3D environment based on basic java graphical applet library.
[ICLR 2024] Official implementation of the paper "Toss: High-quality text-guided novel view synthesis from a single image"
Point Transformer Diffusion is a novel generative model for 3D point cloud generation, which integrates the classical diffusion model and a local self-attention network.
ShapeGPT: 3D Shape Generation with A Unified Multi-modal Language Model, a unified and user-friendly shape-language model
Motion Avatar: Generate Human and Animal Avatars with Arbitrary Motion
Official Code for 'TeMO: Towards Text-Driven 3D Stylization for Multi-Object Meshes' (CVPR 2024)
Zero-shot, text-driven appearance manipulation on multiple views of an object to generate 3D renderings.
3D-GAN able to generate small villages (settlements) on Minecraft
[NeurIPS 2023] VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation
An official implementation of FlexiDreamer: Single Image-to-3D Generation with FlexiCubes.
Official implementation of Customize-It-3D: High-Quality 3D Creation from A Single Image Using Subject-Specific Knowledge Prior
CraftsMan: High-fidelity Mesh Generation with 3D Native Diffusion and Interactive Geometry Refiner
Unofficial Implementation of "Stable Video Diffusion Multi-View"
This is an open collection of state-of-the-art (SOTA), novel Text to X (X can be everything) methods (papers, codes and datasets).
[CVPR 2024] MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation
[NeurIPS 2022] SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping
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