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Found 6 papers, 6 papers with code
Fully Sparse 3D Occupancy Prediction
Occupancy prediction plays a pivotal role in autonomous driving.
SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
Dense detectors typically follow a two-stage pipeline by first constructing a dense BEV feature and then performing object detection in BEV space, which suffers from complex view transformations and high computation cost.
Ranked #5 on
3D Object Detection
on nuScenes Camera Only
StageInteractor: Query-based Object Detector with Cross-stage Interaction
Most of these detectors are trained with one-to-many label assignment strategies.
LinK: Linear Kernel for LiDAR-based 3D Perception
Extending the success of 2D Large Kernel to 3D perception is challenging due to: 1. the cubically-increasing overhead in processing 3D data; 2. the optimization difficulties from data scarcity and sparsity.
Learning Optical Flow and Scene Flow with Bidirectional Camera-LiDAR Fusion
To fuse dense image features and sparse point features, we propose a learnable operator named bidirectional camera-LiDAR fusion module (Bi-CLFM).
Ranked #1 on
Scene Flow Estimation
on KITTI 2015 Scene Flow Test
CamLiFlow: Bidirectional Camera-LiDAR Fusion for Joint Optical Flow and Scene Flow Estimation
In this paper, we study the problem of jointly estimating the optical flow and scene flow from synchronized 2D and 3D data.
Ranked #3 on
Scene Flow Estimation
on Spring
