Looking Inside Out: Anticipating Driver Intent From Videos

1 code implementation • 3 Dec 2023 • Yung-chi Kung, Arthur Zhang, Junmin Wang, Joydeep Biswas

In this work, we propose a novel method of utilizing in-cabin and external camera data to improve state-of-the-art (SOTA) performance in predicting future driver actions.

Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset

2 code implementations • 24 Sep 2023 • Arthur Zhang, Chaitanya Eranki, Christina Zhang, Ji-Hwan Park, Raymond Hong, Pranav Kalyani, Lochana Kalyanaraman, Arsh Gamare, Arnav Bagad, Maria Esteva, Joydeep Biswas

Using our dataset and annotations, we release benchmarks for 3D object detection and 3D semantic segmentation using established metrics.

3D Object Detection 3D Semantic Segmentation +4

Convolutional Bayesian Kernel Inference for 3D Semantic Mapping

2 code implementations • 21 Sep 2022 • Joey Wilson, Yuewei Fu, Arthur Zhang, Jingyu Song, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari

Robotic perception is currently at a cross-roads between modern methods, which operate in an efficient latent space, and classical methods, which are mathematically founded and provide interpretable, trustworthy results.

Bayesian Inference

MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environments

1 code implementation • 14 Mar 2022 • Joey Wilson, Jingyu Song, Yuewei Fu, Arthur Zhang, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari

This work addresses a gap in semantic scene completion (SSC) data by creating a novel outdoor data set with accurate and complete dynamic scenes.