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 776–800 of 1576 papers

TitleStatusHype
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D MappingCode0
Stereo R-CNN based 3D Object Detection for Autonomous DrivingCode0
V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations—0
VolMap: A Real-time Model for Semantic Segmentation of a LiDAR surrounding view—0
Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks—0
Voting for Voting in Online Point Cloud Object Detection—0
Voxel-FPN: multi-scale voxel feature aggregation in 3D object detection from point clouds—0
VoxelNextFusion: A Simple, Unified and Effective Voxel Fusion Framework for Multi-Modal 3D Object Detection—0
VPFNet: Improving 3D Object Detection with Virtual Point based LiDAR and Stereo Data Fusion—0
VPFNet: Voxel-Pixel Fusion Network for Multi-class 3D Object Detection—0
Voxel or Pillar: Exploring Efficient Point Cloud Representation for 3D Object Detection—0
Weak Cube R-CNN: Weakly Supervised 3D Detection using only 2D Bounding Boxes—0
Weakly Supervised Point Clouds Transformer for 3D Object Detection—0
Weighted Unsupervised Learning for 3D Object Detection—0
Which2comm: An Efficient Collaborative Perception Framework for 3D Object Detection—0
X^3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection—0
X3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detection—0
X-view: Non-egocentric Multi-View 3D Object Detector—0
YOLO and K-Means Based 3D Object Detection Method on Image and Point Cloud—0
You Don't Only Look Once: Constructing Spatial-Temporal Memory for Integrated 3D Object Detection and Tracking—0
You Only Label Once: 3D Box Adaptation from Point Cloud to Image via Semi-Supervised Learning—0
You Only Look Bottom-Up for Monocular 3D Object Detection—0
ZFusion: An Effective Fuser of Camera and 4D Radar for 3D Object Perception in Autonomous Driving—0
Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles—0
ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving—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