BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation [PDF]
Multi-sensor fusion is essential for an accurate and reliable autonomous driving system. Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with camera features.
Zhijian Liu +6 more
semanticscholar +1 more source
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion [PDF]
Multi-modality (MM) image fusion aims to render fused images that maintain the merits of different modalities, e.g., functional highlight and detailed textures.
Zixiang Zhao +7 more
semanticscholar +1 more source
LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images [PDF]
Deep learning based fusion methods have been achieving promising performance in image fusion tasks. This is attributed to the network architecture that plays a very important role in the fusion process.
Hui Li +4 more
semanticscholar +1 more source
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving [PDF]
How should representations from complementary sensors be integrated for autonomous driving? Geometry-based sensor fusion has shown great promise for perception tasks such as object detection and motion forecasting.
Aditya Prakash +2 more
semanticscholar +1 more source
Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis [PDF]
In multimodal sentiment analysis (MSA), the performance of a model highly depends on the quality of synthesized embeddings. These embeddings are generated from the upstream process called multimodal fusion, which aims to extract and combine the input ...
Wei Han, Hui Chen, Soujanya Poria
semanticscholar +1 more source
Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review [PDF]
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily available nowadays, which renders researchers an opportunity to tackle ...
Jiaxin Li +6 more
semanticscholar +1 more source
U2Fusion: A Unified Unsupervised Image Fusion Network
This study proposes a novel unified and unsupervised end-to-end image fusion network, termed as U2Fusion, which is capable of solving different fusion problems, including multi-modal, multi-exposure, and multi-focus cases.
Han Xu +4 more
semanticscholar +1 more source
Convolutional Two-Stream Network Fusion for Video Action Recognition [PDF]
Recent applications of Convolutional Neural Networks (ConvNets) for human action recognition in videos have proposed different solutions for incorporating the appearance and motion information.
Christoph Feichtenhofer +2 more
semanticscholar +1 more source
DenseFuse: A Fusion Approach to Infrared and Visible Images [PDF]
In this paper, we present a novel deep learning architecture for infrared and visible images fusion problems. In contrast to conventional convolutional networks, our encoding network is combined with convolutional layers, a fusion layer, and dense block ...
Hui Li, Xiaojun Wu
semanticscholar +1 more source
Multi-Scale Boosted Dehazing Network With Dense Feature Fusion [PDF]
In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature Fusion based on the U-Net architecture. The proposed method is designed based on two principles, boosting and error feedback, and we show that they are suitable for the ...
Hang Dong +6 more
semanticscholar +1 more source

