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 411420 of 1576 papers

TitleStatusHype
AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene UnderstandingCode0
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object DetectionCode2
SDGE: Stereo Guided Depth Estimation for 360^ Camera Sets0
LiRaFusion: Deep Adaptive LiDAR-Radar Fusion for 3D Object DetectionCode1
MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object DetectionCode2
AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision TransformerCode1
Neural Rendering based Urban Scene Reconstruction for Autonomous Driving0
Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration0
Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private SourcesCode0
Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object DetectionCode2
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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