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 1051–1075 of 1576 papers

TitleStatusHype
Group Equivariant BEV for 3D Object Detection—0
Transformer-based stereo-aware 3D object detection from binocular images—0
Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection—0
CrossFusion: Interleaving Cross-modal Complementation for Noise-resistant 3D Object Detection—0
MMDR: A Result Feature Fusion Object Detection Approach for Autonomous System—0
SDVRF: Sparse-to-Dense Voxel Region Fusion for Multi-modal 3D Object Detection—0
PALF: Pre-Annotation and Camera-LiDAR Late Fusion for the Easy Annotation of Point Clouds—0
Sparse Dense Fusion for 3D Object Detection—0
BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo—0
Voxel or Pillar: Exploring Efficient Point Cloud Representation for 3D Object Detection—0
LiDAR-Based 3D Object Detection via Hybrid 2D Semantic Scene GenerationCode0
BugNIST -- a Large Volumetric Dataset for Object Detection under Domain Shift—0
DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving—0
Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver—0
IC-FPS: Instance-Centroid Faster Point Sampling Module for 3D Point-base Object Detection—0
Robo3D: Towards Robust and Reliable 3D Perception against Corruptions—0
BEVFusion4D: Learning LiDAR-Camera Fusion Under Bird's-Eye-View via Cross-Modality Guidance and Temporal Aggregation—0
Unsupervised Adaptation from Repeated Traversals for Autonomous DrivingCode0
Learning to Zoom and Unzoom—0
MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer—0
MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation—0
OcTr: Octree-based Transformer for 3D Object Detection—0
DR.CPO: Diversified and Realistic 3D Augmentation via Iterative Construction, Random Placement, and HPR OcclusionCode0
Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection—0
Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous DrivingCode0
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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