Statistics for topic 3d-object-detection
RepositoryStats tracks 559,026 Github repositories, of these 107 are tagged with the 3d-object-detection topic. The most common primary language for repositories using this topic is Python (93).
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OpenMMLab's next-generation platform for general 3D object detection.
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
Official implementation of the paper " FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything "
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation (ICCV 2023)
Official implementation of the paper " FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything "
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation (ICCV 2023)
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
OpenMMLab's next-generation platform for general 3D object detection.
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
Official repository of ”LION: Linear Group RNN for 3D Object Detection in Point Clouds“
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
Official repository of ”LION: Linear Group RNN for 3D Object Detection in Point Clouds“
Official implementation of the paper " FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything "
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation (ICCV 2023)
GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation [IJCV2023]
OpenMMLab's next-generation platform for general 3D object detection.
[ECCV2024] This is the official implementation of GraphBEV, a BEV multi-modal framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
Official repository of ”LION: Linear Group RNN for 3D Object Detection in Point Clouds“
[ECCV2024] This is the official implementation of GraphBEV, a BEV multi-modal framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
Official repository of ”LION: Linear Group RNN for 3D Object Detection in Point Clouds“
[ECCV 2024] Ray Denoising (RayDN): Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection
Official implementation of the paper " FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything "
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
[ICLR2024] HEAL: An Extensible Framework for Open Heterogeneous Collaborative Perception ➡️ All You Need for Multi-Modality Collaborative Perception!
[AAAI2024] Far3D: Expanding the Horizon for Surround-view 3D Object Detection
Official repository of ”LION: Linear Group RNN for 3D Object Detection in Point Clouds“
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation (ICCV 2023)
OpenMMLab's next-generation platform for general 3D object detection.
Official PyTorch implementation of FB-BEV & FB-OCC - Forward-backward view transformation for vision-centric autonomous driving perception
[CVPR2024] OneFormer3D: One Transformer for Unified Point Cloud Segmentation
[ICCV 2023] SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
[ICCV 2023] SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
[ICCV2023] Official Implementation of "UniTR: A Unified and Efficient Multi-Modal Transformer for Bird’s-Eye-View Representation"