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 701–725 of 1576 papers

TitleStatusHype
PointFusion: Deep Sensor Fusion for 3D Bounding Box EstimationCode0
ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object DetectionCode0
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio MaskingCode0
Improving Generalization Ability for 3D Object Detection by Learning Sparsity-invariant FeaturesCode0
Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous DrivingCode0
3D Object Detection from Point Cloud via Voting Step DiffusionCode0
Context-Aware Dynamic Feature Extraction for 3D Object Detection in Point CloudsCode0
Three-dimensional Backbone Network for 3D Object Detection in Traffic ScenesCode0
BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using DepthCode0
Perspective-aware Convolution for Monocular 3D Object DetectionCode0
IDD-3D: Indian Driving Dataset for 3D Unstructured Road ScenesCode0
Paint and Distill: Boosting 3D Object Detection with Semantic Passing NetworkCode0
SAILOR: Scaling Anchors via Insights into Latent Object RepresentationCode0
HyperMODEST: Self-Supervised 3D Object Detection with Confidence Score FilteringCode0
CVCP-Fusion: On Implicit Depth Estimation for 3D Bounding Box PredictionCode0
OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair NavigationCode0
3D Object Detection From LiDAR Data Using Distance Dependent Feature ExtractionCode0
HV-BEV: Decoupling Horizontal and Vertical Feature Sampling for Multi-View 3D Object DetectionCode0
CT3D++: Improving 3D Object Detection with Keypoint-induced Channel-wise TransformerCode0
AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene UnderstandingCode0
Holistic 3D Scene Parsing and Reconstruction from a Single RGB ImageCode0
OKGR: Occluded Keypoint Generation and Refinement for 3D Object DetectionCode0
Cross-Modal Self-Supervised Learning with Effective Contrastive Units for LiDAR Point CloudsCode0
OBMO: One Bounding Box Multiple Objects for Monocular 3D Object DetectionCode0
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance VotingCode0
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All datasetsnuScenesScanNetV2SUN-RGBD valKITTI Cars EasyKITTI Cars HardnuScenes Camera OnlyKITTI Cars Easy valKITTI Cars Moderate valnuscenes Camera-RadarView-of-Delft (val)KITTI Cars Hard valDAIR-V2X-I

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