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 831840 of 1576 papers

TitleStatusHype
SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point CloudCode1
DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection0
3D Object Aided Self-Supervised Monocular Depth Estimation0
IDMS: Instance Depth for Multi-scale Monocular 3D Object Detection0
BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks0
MGTANet: Encoding Sequential LiDAR Points Using Long Short-Term Motion-Guided Temporal Attention for 3D Object DetectionCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
Attention-Based Depth Distillation with 3D-Aware Positional Encoding for Monocular 3D Object DetectionCode0
BEVUDA: Multi-geometric Space Alignments for Domain Adaptive BEV 3D Object Detection0
Superpoint Transformer for 3D Scene Instance SegmentationCode1
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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