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A suite of image and video neural tokenizers
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
Official implementation of the paper “MagicDriveDiT: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control”
[CVPR 2024] Official implementation of "Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction"
EGSRAL: An Enhanced 3D Gaussian Splatting based Renderer with Automated Labeling for Large-Scale Driving Scene
The official repository for paper "Tora: Trajectory-oriented Diffusion Transformer for Video Generation"
Fine-Grained Open Domain Image Animation with Motion Guidance
Accepted as [NeurIPS 2024] Spotlight Presentation Paper
【三年面试五年模拟】AI算法工程师面试秘籍。涵盖AIGC、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、SLAM、具身智能、元宇宙、AGI等AI行业面试笔试经验与干货知识。
Official PyTorch implementation of TrackDiffusion (https://arxiv.org/abs/2312.00651)
A diffuser implementation of Zero123. Zero-1-to-3: Zero-shot One Image to 3D Object (ICCV23)
UniDrive: Towards Universal Driving Perception Across Camera Configurations
Stable Video Diffusion Training Code and Extensions.
Generative Models by Stability AI
FreeVS: Generative View Synthesis on Free Driving Trajectory
The devkit of the nuScenes dataset.
[ECCV 2024 - Oral] ACE0 is a learning-based structure-from-motion approach that estimates camera parameters of sets of images by learning a multi-view consistent, implicit scene representation.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
Official implementation of "ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis"
Zero-1-to-3: Zero-shot One Image to 3D Object (ICCV 2023)
Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
Nightly release of ControlNet 1.1
[ECCV 2024] DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving
Official implementation of the paper “MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes”
[ICLR24] Official implementation of the paper “MagicDrive: Street View Generation with Diverse 3D Geometry Control”