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[CVPR 2024] LMDrive: Closed-Loop End-to-End Driving with Large Language Models
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Generalized-Controllable Variational Autoencoder (GCVAE)
A spectro-temporal fusion feature, STgram, with MobileFaceNet For more stable Anomalous Sound Detection
A simple pytorch implementation for calculating VAE loss components and annealing KLD loss while training VAEs, especially RNN-based
LAVIS - A One-stop Library for Language-Vision Intelligence
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
[ECCV 2024] Embodied Understanding of Driving Scenarios
This repository collects research papers of large Vision Language Models in Autonomous driving and Intelligent Transportation System. The repository will be continuously updated to track the lates…
[IEEE T-PAMI 2024] All you need for End-to-end Autonomous Driving
(ICCV 2021, Oral) RL and distillation in CARLA using a factorized world model
Implementation of Gaussian Mixture Variational Autoencoder (GMVAE) for Unsupervised Clustering
We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.
About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_
A curated list of awesome LLM/VLM/VLA for Autonomous Driving(LLM4AD) resources (continually updated)
[CVPR 2022] HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction
Pytorch implementation of paper "VectorNet: Encoding HD maps and Agent Dynamics from Vectorized Representation"
A Collection of Variational Autoencoders (VAE) in PyTorch.
[ECCV2020 Oral] Learning Lane Graph Representations for Motion Forecasting
Desktop based tool for viewing, editing and saving road network maps for autonomous vehicle platforms such as Autoware.
Event-based Vision Resources. Community effort to collect knowledge on event-based vision technology (papers, workshops, datasets, code, videos, etc)
The goal of this repo is to make the drone datasets as easy to use as possible. For this purpose we provide source code in Python, which allows the import and visualization of the datasets.
[T-ITS] Driving Behavior Modeling using Naturalistic Human Driving Data with Inverse Reinforcement Learning
Implementations of selected inverse reinforcement learning algorithms.
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Pytorch implementation of convolutional neural network visualization techniques
Open standard for machine learning interoperability