Official inference repo for FLUX.1 models

TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering

The official PyTorch implementation of the paper "Human Motion Diffusion Model"

set prompt to divided region

[CVPR 2024] Official repo for "InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model".

💫 [CVPR 2024] LiDAR4D: Dynamic Neural Fields for Novel Space-time View LiDAR Synthesis

Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering

[CVPR 2024] Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis

[CVPR 2024] Code for SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes

[ECCV 2024] GenAD: Generative End-to-End Autonomous Driving

A collaboration friendly studio for NeRFs

[ECCV 2024] Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

[CVPR 2024] Official implementation of "Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction"

[CVPR 2024, highlight] Dynamic LiDAR Re-simulation using Compositional Neural Fields

LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields

neuralsim: 3D surface reconstruction and simulation based on 3D neural rendering.

[ICCV 2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

[arXiv 2023] DreamGaussian4D: Generative 4D Gaussian Splatting

Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.

[CVPR 2024] GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting

[ICLR 2024 Oral] Generative Gaussian Splatting for Efficient 3D Content Creation

Resources of Neural Rendering

[CVPR2024] NeuRAD: Neural Rendering for Autonomous Driving

A pytorch CUDA extension implementation of instant-ngp (sdf and nerf), with a GUI.

HEDNet (NeurIPS 2023) & SAFDNet (CVPR 2024 Oral)

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

[ECCV 2024] DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving