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 726750 of 1576 papers

TitleStatusHype
Distilling Temporal Knowledge with Masked Feature Reconstruction for 3D Object Detection0
Boosting Deep Neural Networks with Geometrical Prior Knowledge: A Survey0
Distance-Normalized Unified Representation for Monocular 3D Object Detection0
Moby: Empowering 2D Models for Efficient Point Cloud Analytics on the Edge0
MLF-DET: Multi-Level Fusion for Cross-Modal 3D Object Detection0
MMDR: A Result Feature Fusion Object Detection Approach for Autonomous System0
Disentangling Monocular 3D Object Detection0
Disentangling and Vectorization: A 3D Visual Perception Approach for Autonomous Driving Based on Surround-View Fisheye Cameras0
Boosting 3D Object Detection by Simulating Multimodality on Point Clouds0
A Light Perspective for 3D Object Detection0
DisARM: Displacement Aware Relation Module for 3D Detection0
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment0
DirectShape: Direct Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation0
Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention0
ALCN: Adaptive Local Contrast Normalization0
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection0
Dimension Embeddings for Monocular 3D Object Detection0
Digging Into Output Representation for Monocular 3D Object Detection0
BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection0
Diffusion-based 3D Object Detection with Random Boxes0
A Hierarchical Graph Network for 3D Object Detection on Point Clouds0
DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation0
DiffRef3D: A Diffusion-based Proposal Refinement Framework for 3D Object Detection0
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection0
3DLG-Detector: 3D Object Detection via Simultaneous Local-Global Feature Learning0
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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