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 876–900 of 1576 papers

TitleStatusHype
A Survey of Robust 3D Object Detection Methods in Point Clouds—0
A-Teacher: Asymmetric Network for 3D Semi-Supervised Object Detection—0
A two-stage data association approach for 3D Multi-object Tracking—0
Aug3D-RPN: Improving Monocular 3D Object Detection by Synthetic Images with Virtual Depth—0
Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection—0
Auto4D: Learning to Label 4D Objects from Sequential Point Clouds—0
AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection—0
Automatic 3D object detection of Proteins in Fluorescent labeled microscope images with spatial statistical analysis—0
Automatic Map Update Using Dashcam Videos—0
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies—0
AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features—0
A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track—0
A Versatile Multi-View Framework for LiDAR-based 3D Object Detection with Guidance from Panoptic Segmentation—0
BAAI-VANJEE Roadside Dataset: Towards the Connected Automated Vehicle Highway technologies in Challenging Environments of China—0
BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection—0
BEVDetNet: Bird's Eye View LiDAR Point Cloud based Real-time 3D Object Detection for Autonomous Driving—0
BEVDiffuser: Plug-and-Play Diffusion Model for BEV Denoising with Ground-Truth Guidance—0
BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation—0
BEVHeight++: Toward Robust Visual Centric 3D Object Detection—0
BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks—0
BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo—0
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos—0
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection—0
BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection—0
Boosting 3D Object Detection by Simulating Multimodality on Point Clouds—0
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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