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Sensor fusion is an essential topic in many perception systems, such asautonomous driving and robotics. Transformers-based detection head andCNN-based feature encoder to extract features from raw sensor-data has emergedas one of the best performing sensor-fusion 3D-detection-framework, accordingto the dataset leaderboards. In this work we provide an in-depth literaturesurvey of transformer based 3D-object detection task in the recent past,primarily focusing on the sensor fusion. We also briefly go through the Visiontransformers (ViT) basics, so that readers can easily follow through the paper.Moreover, we also briefly go through few of the non-transformer basedless-dominant methods for sensor fusion for autonomous driving. In conclusionwe summarize with sensor-fusion trends to follow and provoke future research.More updated summary can be found at:https://github.com/ApoorvRoboticist/Transformers-Sensor-Fusion

Transformer-Based Sensor Fusion for Autonomous Driving: A Survey