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

Showing 971980 of 1576 papers

TitleStatusHype
Color-aware two-branch DCNN for efficient plant disease classificationCode1
SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and TrackingCode1
Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?0
Self-Supervised 3D Monocular Object Detection by Recycling Bounding Boxes0
LidarMultiNet: Unifying LiDAR Semantic Segmentation, 3D Object Detection, and Panoptic Segmentation in a Single Multi-task Network0
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
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Benchmark Results

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