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Sensor Fusion

21 papers with code ยท Miscellaneous

Sensor Fusion is the broad category of combining various on-board sensors to produce better measurement estimates. These sensors are combined to compliment each other and overcome individual shortcomings.

Source: Real Time Dense Depth Estimation by Fusing Stereo with Sparse Depth Measurements

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Latest papers without code

Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors

14 Jul 2020

Besides the common video and audio sensors, the system also includes a thermal infrared camera, which is shown to be a feasible solution to the drone detection task.

SENSOR FUSION

Camera-Lidar Integration: Probabilistic sensor fusion for semantic mapping

9 Jul 2020

Our approach is capable of using a multi-sensor platform to build a three-dimensional semantic voxelized map that considers the uncertainty of all of the processes involved.

SENSOR FUSION

Sensor Fusion of Camera and Cloud Digital Twin Information for Intelligent Vehicles

8 Jul 2020

With the rapid development of intelligent vehicles and Advanced Driving Assistance Systems (ADAS), a mixed level of human driver engagements is involved in the transportation system.

SENSOR FUSION

Towards Robust Sensor Fusion in Visual Perception

23 Jun 2020

We study the problem of robust sensor fusion in visual perception, especially under the autonomous driving settings.

AUTONOMOUS DRIVING OBJECT DETECTION SENSOR FUSION

Geometry-Aware Instance Segmentation with Disparity Maps

14 Jun 2020

Mask regression is based on 2D, 2. 5D, and 3D ROI using the pseudo-lidar and image-based representations.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION SENSOR FUSION

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies

10 Jun 2020

Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.

3D OBJECT DETECTION AUTONOMOUS DRIVING DEPTH ESTIMATION SENSOR FUSION

PointPainting: Sequential Fusion for 3D Object Detection

CVPR 2020

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

3D OBJECT DETECTION SELF-DRIVING CARS SEMANTIC SEGMENTATION SENSOR FUSION

Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather

CVPR 2020

The fusion of multimodal sensor streams, such as camera, lidar, and radar measurements, plays a critical role in object detection for autonomous vehicles, which base their decision making on these inputs.

AUTONOMOUS VEHICLES DECISION MAKING OBJECT DETECTION SENSOR FUSION

Neural Networks Versus Conventional Filters for Inertial-Sensor-based Attitude Estimation

14 May 2020

Inertial measurement units are commonly used to estimate the attitude of moving objects.

SENSOR FUSION