3D Object Detection
67개 벤치마크 · 논문 1,801편 · 이 태스크의 논문 보기 →
Benchmarks
nuScenes
ScanNetV2
SUN-RGBD val
KITTI Cars Easy
KITTI Cars Hard
nuScenes Camera Only
KITTI Cyclists Moderate
KITTI Cyclists Easy
KITTI Cyclists Hard
KITTI Pedestrians Moderate
KITTI Cars Easy val
KITTI Cars Moderate val
View-of-Delft (val)
nuscenes Camera-Radar
KITTI Cars Hard val
DAIR-V2X-I
KITTI Pedestrians Easy
KITTI Pedestrians Hard
Rope3D
Waymo Open Dataset
SUN-RGBD
waymo vehicle
S3DIS
nuScenes LiDAR only
waymo cyclist
waymo pedestrian
Argoverse
V2XSet
DTTD-Mobile
OPV2V
SimBEV
V2X-SIM
TruckScenes
ARKitScenes
Aria Everyday Objects
Aria Synthetic Environments
KITTI Cyclist Easy val
KITTI Cyclist Hard val
KITTI Cyclist Moderate val
KITTI Pedestrian Easy val
KITTI Pedestrian Hard val
3RScan
MultiScan
ScanNet++
aiMotive Dataset
ONCE
Argoverse2
DAIR-V2X
Spiideo SoccerNet SynLoc
waymo all_ns
Cityscapes 3D
Clear Weather
Dense Fog
Heavy Snowfall
IRV2V
KITTI Pedestrian
KITTI Pedestrian Easy
KITTI Pedestrian Hard
Light Snowfall
NYU Depth v2
nuScenes-F
nuScenes-FB
Most implemented
YOLO9000: Better, Faster, Stronger
Objects as Points
Frustum PointNets for 3D Object Detection from RGB-D Data
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions
PointPillars: Fast Encoders for Object Detection from Point Clouds
Papers
NeuroSymbEAD: A Large Scale Neuro-Symbolic Caption Dataset for Omni-Directional Embodied Autonomous Driving
This paper introduces NeuroSymbEAD, a large-scale neuro-symbolic caption dataset featuring an ego-centric knowledge graph (KG) of static and dynamic objects annotated with classes, categories, heading directions, orienta…
Scene Understanding3D Object DetectionAutonomous DrivingSimFuse3D: Source-Guided Target Simulation and Confidence-Guided Multi-Stage Localization Reweighting for Cross-Platform 3D Object Detection
Changes in sensor height and viewpoint alter object-level point distributions, making cross-platform LiDAR unsupervised domain adaptation (UDA) difficult. Self-training uses labeled source scans and unlabeled target scan…
Unsupervised Domain Adaptation3D Object DetectionLucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling
Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observed, giving robot simulation and embodied AI a simulation-ready replica of the real environment whose obj…
3D Object DetectionPose EstimationQwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving
We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of the pretrained vision-language model (VLM) and integrates 3D percep…
Visual Question AnsweringScene Understanding3D Object DetectionAutonomous DrivingTADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection
Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features into a common space that is adaptive for all the tasks. We present a nov…
3D Object DetectionOpen-Vocabulary 3D Object Detection with Co-Distillation Discovery and Dual Guidance Robust Training
Recently, open-vocabulary 3D object detection (3D-OVD) has gained increasing attention for its ability to detect unseen objects in 3D scenes. Existing approaches typically adopt a two-stage pipeline that first discovers …
3D Object Detection