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Found 10 papers, 4 papers with code
CMP: Cooperative Motion Prediction with Multi-Agent Communication
Building on top of cooperative perception, this paper explores the feasibility and effectiveness of cooperative motion prediction.
Embodied Understanding of Driving Scenarios
Hereby, we introduce the Embodied Language Model (ELM), a comprehensive framework tailored for agents' understanding of driving scenes with large spatial and temporal spans.
WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting
To study the effect of these modular approaches, design new paradigms that mitigate these limitations, and accelerate the development of end-to-end motion forecasting models, we augment the Waymo Open Motion Dataset (WOMD) with large-scale, high-quality, diverse LiDAR data for the motion forecasting task.
COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehicles
To evaluate our model, we develop AutoCastSim, a network-augmented driving simulation framework with example accident-prone scenarios.
Personalized Federated Learning of Driver Prediction Models for Autonomous Driving
Autonomous vehicles (AVs) must interact with a diverse set of human drivers in heterogeneous geographic areas.
ML-EXray: Visibility into ML Deployment on the Edge
The key challenge is that there is not much visibility into ML inference execution on edge devices, and very little awareness of potential issues during the edge deployment process.
FedML: A Research Library and Benchmark for Federated Machine Learning
Federated learning (FL) is a rapidly growing research field in machine learning.
MCAL: Minimum Cost Human-Machine Active Labeling
These services rely on human annotation, which can be prohibitively expensive.
On Localizing a Camera from a Single Image
Public cameras often have limited metadata describing their attributes.
Satyam: Democratizing Groundtruth for Machine Vision
The democratization of machine learning (ML) has led to ML-based machine vision systems for autonomous driving, traffic monitoring, and video surveillance.
