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SOTA
三维物体检测
3D Object Detection On Nuscenes Camera Only
3D Object Detection On Nuscenes Camera Only
评估指标
Future Frame
NDS
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Future Frame
NDS
Paper Title
Repository
Far3D
false
68.7
Far3D: Expanding the Horizon for Surround-view 3D Object Detection
-
BEVDet4D
false
56.9
BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection
-
CAPE
false
62.8
CAPE: Camera View Position Embedding for Multi-View 3D Object Detection
-
BEVDepth-pure
false
60.9
BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection
-
PETRv2-pure
false
59.2
PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images
-
SA-BEV
false
62.4
SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection
-
SOLOFusion-pure
false
61.9
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
-
StreamPETR-Large
false
67.6
Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection
-
HoP
yes
68.5
Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction
-
BEVStereo
false
61.0
BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo
-
RayDN
false
68.6
Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection
-
BEVDistill
false
59.4
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection
-
PolarFormer
false
57.2
PolarFormer: Multi-camera 3D Object Detection with Polar Transformer
-
SparseBEV (V2-99)
yes
67.5
SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
-
GeoBEV (V2-99)
false
66.2
GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object Detection
-
BEVFormer v2 (InternImage-XL)
yes
63.4
BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision
-
VCD-A
false
67.2
Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection
-
SeaBird
false
59.7
SeaBird: Segmentation in Bird's View with Dice Loss Improves Monocular 3D Detection of Large Objects
-
BEVFormer
false
56.9
BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
-
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