Search Results for author: Sourabh Vora

Found 8 papers, 3 papers with code

Proposal-free Lidar Panoptic Segmentation with Pillar-level Affinity

no code implementations19 Apr 2022 Qi Chen, Sourabh Vora

We propose a simple yet effective proposal-free architecture for lidar panoptic segmentation.

Classification Clustering +4

PolarStream: Streaming Object Detection and Segmentation with Polar Pillars

no code implementations NeurIPS 2021 Qi Chen, Sourabh Vora, Oscar Beijbom

Recent works recognized lidars as an inherently streaming data source and showed that the end-to-end latency of lidar perception models can be reduced significantly by operating on wedge-shaped point cloud sectors rather then the full point cloud.

Object object-detection +1

PolarStream: Streaming Lidar Object Detection and Segmentation with Polar Pillars

no code implementations14 Jun 2021 Qi Chen, Sourabh Vora, Oscar Beijbom

Recent works recognized lidars as an inherently streaming data source and showed that the end-to-end latency of lidar perception models can be reduced significantly by operating on wedge-shaped point cloud sectors rather then the full point cloud.

LIDAR Semantic Segmentation object-detection +1

PointPainting: Sequential Fusion for 3D Object Detection

4 code implementations CVPR 2020 Sourabh Vora, Alex H. Lang, Bassam Helou, Oscar Beijbom

Surprisingly, lidar-only methods outperform fusion methods on the main benchmark datasets, suggesting a gap in the literature.

3D Object Detection Object +5

Driver Gaze Zone Estimation using Convolutional Neural Networks: A General Framework and Ablative Analysis

no code implementations8 Feb 2018 Sourabh Vora, Akshay Rangesh, Mohan M. Trivedi

Finally, we evaluate our best performing model on the publicly available Columbia Gaze Dataset comprising of images from 56 subjects with varying head pose and gaze directions.

Autonomous Vehicles

Dynamics of Driver's Gaze: Explorations in Behavior Modeling & Maneuver Prediction

no code implementations31 Jan 2018 Sujitha Martin, Sourabh Vora, Kevan Yuen, Mohan M. Trivedi

The study and modeling of driver's gaze dynamics is important because, if and how the driver is monitoring the driving environment is vital for driver assistance in manual mode, for take-over requests in highly automated mode and for semantic perception of the surround in fully autonomous mode.

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