Search Results for author: Simon Suo

Found 9 papers, 2 papers with code

Learning Realistic Traffic Agents in Closed-loop

no code implementations2 Nov 2023 Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, Raquel Urtasun

Our experiments show that RTR learns more realistic and generalizable traffic simulation policies, achieving significantly better tradeoffs between human-like driving and traffic compliance in both nominal and long-tail scenarios.

Imitation Learning Reinforcement Learning (RL)

MixSim: A Hierarchical Framework for Mixed Reality Traffic Simulation

no code implementations CVPR 2023 Simon Suo, Kelvin Wong, Justin Xu, James Tu, Alexander Cui, Sergio Casas, Raquel Urtasun

Towards this goal, we propose to leverage the wealth of interesting scenarios captured in the real world and make them reactive and controllable to enable closed-loop SDV evaluation in what-if situations.

Mixed Reality

GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting

no code implementations4 Nov 2022 Alexander Cui, Sergio Casas, Kelvin Wong, Simon Suo, Raquel Urtasun

However, this approach is computationally expensive for multi-agent prediction as inference needs to be run for each agent.

Motion Forecasting

Deep Parametric Continuous Convolutional Neural Networks

no code implementations CVPR 2018 Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, Raquel Urtasun

Standard convolutional neural networks assume a grid structured input is available and exploit discrete convolutions as their fundamental building blocks.

 Ranked #1 on Semantic Segmentation on S3DIS Area5 (Number of params metric)

Motion Estimation Point Cloud Segmentation +1

End-to-end Interpretable Neural Motion Planner

1 code implementation CVPR 2019 Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, Raquel Urtasun

In this paper, we propose a neural motion planner (NMP) for learning to drive autonomously in complex urban scenarios that include traffic-light handling, yielding, and interactions with multiple road-users.

TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors

1 code implementation CVPR 2021 Simon Suo, Sebastian Regalado, Sergio Casas, Raquel Urtasun

We show TrafficSim generates significantly more realistic and diverse traffic scenarios as compared to a diverse set of baselines.

Common Sense Reasoning Data Augmentation

StrObe: Streaming Object Detection from LiDAR Packets

no code implementations12 Nov 2020 Davi Frossard, Simon Suo, Sergio Casas, James Tu, Rui Hu, Raquel Urtasun

In this paper we propose StrObe, a novel approach that minimizes latency by ingesting LiDAR packets and emitting a stream of detections without waiting for the full sweep to be built.

Object object-detection +1

Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

no code implementations ECCV 2020 Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun

In order to plan a safe maneuver an autonomous vehicle must accurately perceive its environment, and understand the interactions among traffic participants.

Motion Forecasting Motion Planning

The Importance of Prior Knowledge in Precise Multimodal Prediction

no code implementations4 Jun 2020 Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun

Towards this goal, we design a framework that leverages REINFORCE to incorporate non-differentiable priors over sample trajectories from a probabilistic model, thus optimizing the whole distribution.

Motion Forecasting Motion Planning

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