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 826–850 of 1576 papers

TitleStatusHype
3D Object Detection Using Scale Invariant and Feature Reweighting Networks—0
3D Object Detection With Latent Support Surfaces—0
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection—0
3D-SSD: Learning Hierarchical Features from RGB-D Images for Amodal 3D Object Detection—0
3DS-SLAM: A 3D Object Detection based Semantic SLAM towards Dynamic Indoor Environments—0
Enabling 3D Object Detection with a Low-Resolution LiDAR—0
3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection—0
3M3D: Multi-view, Multi-path, Multi-representation for 3D Object Detection—0
A 3D Object Detection and Pose Estimation Pipeline Using RGB-D Images—0
AA3DNet: Attention Augmented Real Time 3D Object Detection—0
Accelerating Federated Edge Learning via Topology Optimization—0
Accurate and Real-time Pseudo Lidar Detection: Is Stereo Neural Network Really Necessary?—0
Accurate Cutting-point Estimation for Robotic Lychee Harvesting through Geometry-aware Learning—0
Accurate Monocular Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving—0
Accurate Monocular 3D Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving—0
Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device—0
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search—0
ActFormer: Scalable Collaborative Perception via Active Queries—0
Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detection—0
Adapting Object Detectors with Conditional Domain Normalization—0
Adaptive and Azimuth-Aware Fusion Network of Multimodal Local Features for 3D Object Detection—0
AdaptiveShape: Solving Shape Variability for 3D Object Detection with Geometry Aware Anchor Distributions—0
A Density-Aware PointRCNN for 3D Object Detection in Point Clouds—0
Adv3D: Generating 3D Adversarial Examples for 3D Object Detection in Driving Scenarios with NeRF—0
Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey—0
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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