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 101–150 of 1576 papers

TitleStatusHype
Virtual Sparse Convolution for Multimodal 3D Object DetectionCode2
Pillar R-CNN for Point Cloud 3D Object DetectionCode2
DSVT: Dynamic Sparse Voxel Transformer with Rotated SetsCode2
Argoverse 2: Next Generation Datasets for Self-Driving Perception and ForecastingCode2
FocalFormer3D: Focusing on Hard Instance for 3D Object DetectionCode2
MegaPose: 6D Pose Estimation of Novel Objects via Render & CompareCode2
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world LearningCode2
Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal FusionCode2
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object DetectionCode2
Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence MapsCode2
BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal StereoCode2
CenterFormer: Center-based Transformer for 3D Object DetectionCode2
DeepInteraction: 3D Object Detection via Modality InteractionCode2
PolarMix: A General Data Augmentation Technique for LiDAR Point CloudsCode2
Monocular 3D Object Detection with Depth from MotionCode2
Omni3D: A Large Benchmark and Model for 3D Object Detection in the WildCode2
DEVIANT: Depth EquiVarIAnt NeTwork for Monocular 3D Object DetectionCode2
Fully Sparse 3D Object DetectionCode2
CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse TransformersCode2
LargeKernel3D: Scaling up Kernels in 3D Sparse CNNsCode2
BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object DetectionCode2
Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy AutoencodersCode2
3D Object Detection for Autonomous Driving: A Comprehensive SurveyCode2
K-Radar: 4D Radar Object Detection for Autonomous Driving in Various Weather ConditionsCode2
LinK3D: Linear Keypoints Representation for 3D LiDAR Point CloudCode2
Unifying Voxel-based Representation with Transformer for 3D Object DetectionCode2
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-trainingCode2
BEVFusion: A Simple and Robust LiDAR-Camera Fusion FrameworkCode2
BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous DrivingCode2
PillarNet: Real-Time and High-Performance Pillar-based 3D Object DetectionCode2
Surface Representation for Point CloudsCode2
TJ4DRadSet: A 4D Radar Dataset for Autonomous DrivingCode2
Focal Sparse Convolutional Networks for 3D Object DetectionCode2
DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
Multi-Class Road User Detection With 3+1D Radar in the View-of-Delft DatasetCode2
Image-to-Lidar Self-Supervised Distillation for Autonomous Driving DataCode2
LiDAR Snowfall Simulation for Robust 3D Object DetectionCode2
MonoDETR: Depth-guided Transformer for Monocular 3D Object DetectionCode2
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with TransformersCode2
V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision TransformerCode2
Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point CloudsCode2
Sparse Fuse Dense: Towards High Quality 3D Detection with Depth CompletionCode2
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with TransformersCode2
SoftGroup for 3D Instance Segmentation on Point CloudsCode2
BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-ViewCode2
Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose AnnotationsCode2
Searching Efficient 3D Architectures with Sparse Point-Voxel ConvolutionCode2
Generative Sparse Detection Networks for 3D Single-shot Object DetectionCode2
Center-based 3D Object Detection and TrackingCode2
Star-convex Polyhedra for 3D Object Detection and Segmentation in MicroscopyCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78—Unverified
2MegFusionNDS0.77—Unverified
3MMFusion-eNDS0.77—Unverified
4BEVFusion-eNDS0.76—Unverified
5RacoonPowerNDS0.76—Unverified
6DeepInteraction-largeNDS0.76—Unverified
7DeepInteraction-eNDS0.76—Unverified
8FusionVPENDS0.75—Unverified
9FocalFormer3D-FNDS0.75—Unverified
10CenterPoint-FusionNDS0.75—Unverified