Ben Caine — accepted AI-conference papers

2024

CausalAgents: A Robustness Benchmark for Motion Forecasting

Liting Sun, Rebecca Roelofs, Ben Caine, Khaled S. Refaat, Ben Sapp, Scott Ettinger +1

ICRA 2024poster

As machine learning models become increasingly prevalent in motion forecasting for autonomous vehicles (AVs), it is critical to ensure that model predictions are safe and reliable. In this paper, we examine the robustness of motion forecasting to non-causal perturbations. We construct a new benchmar…

Cited by 3 Source ↗Scholar ↗

2022

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

Yingwei Li, Adams Wei Yu, Tianjian Meng, Ben Caine, Jiquan Ngiam, Daiyi Peng +6

CVPR 2022poster

Lidars and cameras are critical sensors that provide complementary information for 3D detection in autonomous driving. While prevalent multi-modal methods simply decorate raw lidar point clouds with camera features and feed them directly to existing 3D detection models, our study shows that fusing c…

Cited by 476 PDF ↗code ↗Scholar ↗