The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge

06/28/2023
by   Cheng Qian, et al.
0

In this technical report, we present the 2nd place solution of 2023 Waymo Open Sim Agents Challenge (WOSAC)[4]. We propose a simple yet effective autoregressive method for simulating multi-agent behaviors, which is built upon a well-known multimodal motion forecasting framework called Motion Transformer (MTR)[5] with postprocessing algorithms applied. Our submission named MTR+++ achieves 0.4697 on the Realism Meta metric in 2023 WOSAC. Besides, a modified model based on MTR named MTR_E is proposed after the challenge, which has a better score 0.4911 and is ranked the 3rd on the leaderboard of WOSAC as of June 25, 2023.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/20/2023

Multiverse Transformer: 1st Place Solution for Waymo Open Sim Agents Challenge 2023

This technical report presents our 1st place solution for the Waymo Open...
research
09/20/2022

MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge – Motion Prediction

In this report, we present the 1st place solution for motion prediction ...
research
12/15/2020

Enhance Multimodal Transformer With External Label And In-Domain Pretrain: Hateful Meme Challenge Winning Solution

Hateful meme detection is a new research area recently brought out that ...
research
06/30/2022

TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction

This technical report presents an effective method for motion prediction...
research
07/02/2022

Golfer: Trajectory Prediction with Masked Goal Conditioning MnM Network

Transformers have enabled breakthroughs in NLP and computer vision, and ...
research
06/05/2023

MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion

We present MotionDiffuser, a diffusion based representation for the join...
research
12/13/2021

5th Place Solution for VSPW 2021 Challenge

In this article, we introduce the solution we used in the VSPW 2021 Chal...

Please sign up or login with your details

Forgot password? Click here to reset