Multimodal learning with transformers: A survey
Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …
Delivering arbitrary-modal semantic segmentation
Multimodal fusion can make semantic segmentation more robust. However, fusing an
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
CMX: Cross-modal fusion for RGB-X semantic segmentation with transformers
Scene understanding based on image segmentation is a crucial component of autonomous
vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting …
vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting …
Cagroup3d: Class-aware grou** for 3d object detection on point clouds
We present a novel two-stage fully sparse convolutional 3D object detection framework,
named CAGroup3D. Our proposed method first generates some high-quality 3D proposals …
named CAGroup3D. Our proposed method first generates some high-quality 3D proposals …
From sparse to soft mixtures of experts
J Puigcerver, C Riquelme, B Mustafa… - ar** perception systems capable of
making accurate, robust, and rapid decisions to interpret the driving environment effectively …
making accurate, robust, and rapid decisions to interpret the driving environment effectively …