SOTAVerified

3D Object Detection

3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.

( Image credit: AVOD )

Papers

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Showing 501–525 of 1576 papers

TitleStatusHype
HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point CloudsCode1
Dynamic V2X Autonomous Perception from Road-to-Vehicle Vision—0
ODM3D: Alleviating Foreground Sparsity for Semi-Supervised Monocular 3D Object DetectionCode0
DiffRef3D: A Diffusion-based Proposal Refinement Framework for 3D Object Detection—0
MVFAN: Multi-View Feature Assisted Network for 4D Radar Object Detection—0
Leveraging Vision-Centric Multi-Modal Expertise for 3D Object DetectionCode3
GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object DetectionCode1
Pre-Training LiDAR-Based 3D Object Detectors Through ColorizationCode0
Fuzzy-NMS: Improving 3D Object Detection with Fuzzy Classification in NMS—0
EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye ViewCode1
RTNH+: Enhanced 4D Radar Object Detection Network using Combined CFAR-based Two-level Preprocessing and Vertical Encoding—0
Towards Generalizable Multi-Camera 3D Object Detection via Perspective DebiasingCode1
MonoSKD: General Distillation Framework for Monocular 3D Object Detection via Spearman Correlation CoefficientCode1
Multimodal Object Query Initialization for 3D Object Detection—0
Open-CRB: Towards Open World Active Learning for 3D Object DetectionCode1
UniPAD: A Universal Pre-training Paradigm for Autonomous DrivingCode2
PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training ParadigmCode2
GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detection—0
Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous DrivingCode1
3DS-SLAM: A 3D Object Detection based Semantic SLAM towards Dynamic Indoor Environments—0
V2X-AHD:Vehicle-to-Everything Cooperation Perception via Asymmetric Heterogenous Distillation NetworkCode0
Uni3DETR: Unified 3D Detection TransformerCode1
CoBEVFusion: Cooperative Perception with LiDAR-Camera Bird's-Eye View Fusion—0
Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems—0
Anyview: Generalizable Indoor 3D Object Detection with Variable Frames—0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MMFusion-eNDS0.77—Unverified
3MegFusionNDS0.77—Unverified
4RacoonPowerNDS0.76—Unverified
5BEVFusion-eNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8DAANDS0.75—Unverified
9FusionVPENDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified