# DSERT-RoLL: Robust Multi-Modal Perception for Diverse Driving Conditions with Stereo Event-RGB-Thermal Cameras, 4D Radar, and Dual-LiDAR

Source: [DSERT-RoLL: Robust Multi-Modal Perception for Diverse Driving Conditions with Stereo Event-RGB-Thermal Cameras, 4D Radar, and Dual-LiDAR](<https://www.sota2.com/research/paper/69d48f657d0172140ec74173>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-04-08T05:00:04.658Z

Authors: Hoonhee Cho, Jae-Young Kang, Yuhwan Jeong, Yunseo Yang, Wonyoung Lee, Youngho Kim, Kuk-Jin Yoon

Published: 2026-04-04T11:03:16.000Z

## Abstract

In this paper, we present DSERT-RoLL, a driving dataset that incorporates stereo event, RGB, and thermal cameras together with 4D radar and dual LiDAR, collected across diverse weather and illumination conditions. The dataset provides precise 2D and 3D bounding boxes with track IDs and ego vehicle odometry, enabling fair comparisons within and across sensor combinations. It is designed to alleviate data scarcity for novel sensors such as event cameras and 4D radar and to support systematic studies of their behavior. We establish unified 3D and 2D benchmarks that enable direct comparison of characteristics and strengths across sensor families and within each family. We report baselines for representative single modality and multimodal methods and provide protocols that encourage research on different fusion strategies and sensor combinations. In addition, we propose a fusion framework that integrates sensor specific cues into a unified feature space and improves 3D detection robustness under varied weather and lighting.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [3D Object Detection on DSERT-RoLL official (test)](<https://www.sota2.com/research/sota/3d-object-detection-on-dsert-roll-official-test.md>): 3D Object Detection; DSERT-RoLL official (test); mAP (Clear): 90.3.

- [2D Object Detection on DSERT-RoLL](<https://www.sota2.com/research/sota/2d-object-detection-on-dsert-roll.md>): 2D Object Detection; DSERT-RoLL; Detection Score (Clear): not recorded.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2604.03685>)

[PDF](<https://arxiv.org/pdf/2604.03685.pdf>)