arXiv:2004.13822
공식 코드 · Papers with Code
A Baseline for the Commands For Autonomous Vehicles Challenge
원문 초록
The Commands For Autonomous Vehicles (C4AV) challenge requires participants to solve an object referral task in a real-world setting. More specifically, we consider a scenario where a passenger can pass free-form natural language commands to a self-driving car. This problem is particularly challenging, as the language is much less constrained compared to existing benchmarks, and object references are often implicit. The challenge is based on the recent \texttt{Talk2Car} dataset. This document provides a technical overview of a model that we released to help participants get started in the competition. The code can be found at https://github.com/talk2car/Talk2Car.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Edge-Enabled Collaborative Object Detection for Real-Time Multi-Vehicle Perception
Camera-Only 3D Panoptic Scene Completion for Autonomous Driving through Differentiable Object Shapes
Object detection in adverse weather conditions for autonomous vehicles using Instruct Pix2Pix
PaniCar: Securing the Perception of Advanced Driving Assistance Systems Against Emergency Vehicle Lighting
Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR
RoHOI: Robustness Benchmark for Human-Object Interaction Detection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.