yoershine

MiniGPT-4

Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)

Grounded-Segment-Anything

Grounded-SAM: Marrying Grounding-DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

Segment-and-Track-Anything

An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.

co-tracker

CoTracker is a model for tracking any point (pixel) on a video.

omnimotion

Semantic-SAM

Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"

dm-vio

Source code for the paper DM-VIO: Delayed Marginalization Visual-Inertial Odometry

mars

MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving

street_gaussians

Code for "Street Gaussians for Modeling Dynamic Urban Scenes"

RepViT

RepViT: Revisiting Mobile CNN From ViT Perspective [CVPR 2024] and RepViT-SAM: Towards Real-Time Segmenting Anything

neuralsim

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

DrivingDiffusion

Layout-Guided multi-view driving scene video generation with latent diffusion model

EmerNeRF

PyTorch Implementation of EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision

READ

AAAI2023，implementation of "READ: Large-Scale Neural Scene Rendering for Autonomous Driving", the experimental results are significantly better than Nerf-based methods

sphinx-autoapi

A new approach to API documentation in Sphinx.

cryptoauthlib

Library for interacting with the Crypto Authentication secure elements

anything_in_anyscene

SelfOcc

[CVPR 2024] SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction

Drive-WM

[CVPR 2024] A world model for autonomous driving.

Forge_VFM4AD

A comprehensive survey of forging vision foundation models for autonomous driving, including challenges, methodologies, and opportunities.

NeuRAD

NeuRAD: Neural Rendering for Autonomous Driving

OASim

OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving

DrivingGaussian

[CVPR 2024] DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes

WidthFormer

WidthFormer: Toward Efficient Transformer-based BEV View Transformation

panacea

[CVPR2024] Official Repository of Paper "Panacea: Panoramic and Controllable Video Generation for Autonomous Driving"

UC-NeRF

[ICLR2024] the official pytorch implementation of UC-NeRF

zod

Software Development Kit for the Zenseact Open Dataset (ZOD)

PowerBEV

POWERBEV, a novel and elegant vision-based end-to-end framework that only consists of 2D convolutional layers to perform perception and forecasting of multiple objects in BEVs.

MIM4D

MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation Learning