Papers with Code 아카이브
Bird's-Eye View Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Epipolar Attention Field Transformers for Bird's Eye View Semantic Segmentation
Progressive Query Refinement Framework for Bird's-Eye-View Semantic Segmentation from Surrounding Images
Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks
Improving Bird's Eye View Semantic Segmentation by Task Decomposition
Residual Graph Convolutional Network for Bird's-Eye-View Semantic Segmentation
PointBeV: A Sparse Approach to BeV Predictions
Semi-Supervised Learning for Visual Bird's Eye View Semantic Segmentation
A Cross-Scale Hierarchical Transformer with Correspondence-Augmented Attention for inferring Bird's-Eye-View Semantic Segmentation
TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception
Model-Based Imitation Learning for Urban Driving
ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers
LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation
Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?
PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images
Cross-view Transformers for real-time Map-view Semantic Segmentation
BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
BEVSegFormer: Bird's Eye View Semantic Segmentation From Arbitrary Camera Rigs
FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Cameras
Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D
BEV-Seg: Bird's Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud
LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands, Water and Roads from Aerial Imagery
Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.