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 741–750 of 1576 papers

TitleStatusHype
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection—0
Dimension Embeddings for Monocular 3D Object Detection—0
Digging Into Output Representation for Monocular 3D Object Detection—0
BiCo-Fusion: Bidirectional Complementary LiDAR-Camera Fusion for Semantic- and Spatial-Aware 3D Object Detection—0
Diffusion-based 3D Object Detection with Random Boxes—0
A Hierarchical Graph Network for 3D Object Detection on Point Clouds—0
DifFUSER: Diffusion Model for Robust Multi-Sensor Fusion in 3D Object Detection and BEV Segmentation—0
DiffRef3D: A Diffusion-based Proposal Refinement Framework for 3D Object Detection—0
Bi3D: Bi-domain Active Learning for Cross-domain 3D Object Detection—0
3DLG-Detector: 3D Object Detection via Simultaneous Local-Global Feature Learning—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