Bird's-Eye View Semantic Segmentation
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Benchmarks
Most implemented
BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers
Cross-view Transformers for real-time Map-view Semantic Segmentation
Papers
SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset
Bird's-eye view (BEV) perception has garnered significant attention in autonomous driving in recent years, in part because BEV representation facilitates multi-modal sensor fusion. BEV representation enables a variety of…
3D Object DetectionAutonomous DrivingBEV SegmentationBird's-Eye View Semantic Segmentation+3Epipolar Attention Field Transformers for Bird's Eye View Semantic Segmentation
Spatial understanding of the semantics of the surroundings is a key capability needed by autonomous cars to enable safe driving decisions. Recently, purely vision-based solutions have gained increasing research interest.…
Bird's-Eye View Semantic SegmentationSemantic SegmentationProgressive Query Refinement Framework for Bird's-Eye-View Semantic Segmentation from Surrounding Images
Expressing images with Multi-Resolution (MR) features has been widely adopted in many computer vision tasks. In this paper, we introduce the MR concept into Bird's-Eye-View (BEV) semantic segmentation for autonomous driv…
Autonomous DrivingBird's-Eye View Semantic SegmentationSemantic SegmentationUncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks
The fusion of raw features from multiple sensors on an autonomous vehicle to create a Bird's Eye View (BEV) representation is crucial for planning and control systems. There is growing interest in using deep learning mod…
Autonomous DrivingBEV SegmentationBird's-Eye View Semantic SegmentationSegmentation+2Improving Bird's Eye View Semantic Segmentation by Task Decomposition
Semantic segmentation in bird's eye view (BEV) plays a crucial role in autonomous driving. Previous methods usually follow an end-to-end pipeline, directly predicting the BEV segmentation map from monocular RGB inputs. H…
Autonomous DrivingBEV SegmentationBird's-Eye View Semantic SegmentationDepth Estimation+2Residual Graph Convolutional Network for Bird's-Eye-View Semantic Segmentation
Retrieving spatial information and understanding the semantic information of the surroundings are important for Bird's-Eye-View (BEV) semantic segmentation. In the application of autonomous driving, autonomous vehicles n…
Autonomous DrivingAutonomous VehiclesBird's-Eye View Semantic SegmentationData Augmentation+2