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BEV Segmentation

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Showing 26–44 of 44 papers

TitleStatusHype
U-BEV: Height-aware Bird's-Eye-View Segmentation and Neural Map-based Relocalization—0
Focus on BEV: Self-calibrated Cycle View Transformation for Monocular Birds-Eye-View Segmentation—0
GitNet: Geometric Prior-based Transformation for Birds-Eye-View Segmentation—0
Unlocking Past Information: Temporal Embeddings in Cooperative Bird's Eye View Prediction—0
OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation—0
PCT: Perspective Cue Training Framework for Multi-Camera BEV Segmentation—0
BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout—0
PointBeV: A Sparse Approach for BeV Predictions—0
PointBeV: A Sparse Approach to BeV Predictions—0
RESAR-BEV: An Explainable Progressive Residual Autoregressive Approach for Camera-Radar Fusion in BEV Segmentation—0
X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentation—0
Self-Supervised Pre-training with Combined Datasets for 3D Perception in Autonomous Driving—0
X-Align++: cross-modal cross-view alignment for Bird's-eye-view segmentation—0
TempBEV: Improving Learned BEV Encoders with Combined Image and BEV Space Temporal Aggregation—0
Divide and Conquer: Improving Multi-Camera 3D Perception with 2D Semantic-Depth Priors and Input-Dependent Queries—0
Towards Viewpoint Robustness in Bird's Eye View Segmentation—0
NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World ModelsCode0
4D-ROLLS: 4D Radar Occupancy Learning via LiDAR SupervisionCode0
BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous DrivingCode0
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