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 601–625 of 1576 papers

TitleStatusHype
Group-Free 3D Object Detection via TransformersCode1
FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective View—0
CMDA: Cross-Modal and Domain Adversarial Adaptation for LiDAR-Based 3D Object Detection—0
A 3D Object Detection and Pose Estimation Pipeline Using RGB-D Images—0
False Positive Sampling-based Data Augmentation for Enhanced 3D Object Detection Accuracy—0
ClusterFusion: Leveraging Radar Spatial Features for Radar-Camera 3D Object Detection in Autonomous Vehicles—0
FALO: Fast and Accurate LiDAR 3D Object Detection on Resource-Constrained Devices—0
Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation—0
Clusterformer: Cluster-based Transformer for 3D Object Detection in Point Clouds—0
3D Object Detection and High-Resolution Traffic Parameters Extraction Using Low-Resolution LiDAR Data—0
Exploring the Capabilities and Limits of 3D Monocular Object Detection -- A Study on Simulation and Real World Data—0
Exploring Geometry-Aware Contrast and Clustering Harmonization for Self-Supervised 3D Object Detection—0
Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts—0
Exploring Domain Shift on Radar-Based 3D Object Detection Amidst Diverse Environmental Conditions—0
CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow—0
CleverDistiller: Simple and Spatially Consistent Cross-modal Distillation—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving—0
3D Object Detection and Instance Segmentation from 3D Range and 2D Color Images—0
Exploring 2D Data Augmentation for 3D Monocular Object Detection—0
A Review of 3D Object Detection with Vision-Language Models—0
Class-Aware PillarMix: Can Mixed Sample Data Augmentation Enhance 3D Object Detection with Radar Point Clouds?—0
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection—0
3M3D: Multi-view, Multi-path, Multi-representation for 3D Object Detection—0
Weakly Supervised 3D Object Detection with Multi-Stage Generalization—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