Search Results for author:
Found 10 papers, 4 papers with code
MonoJSG: Joint Semantic and Geometric Cost Volume for Monocular 3D Object Detection
Based on the object depth, the dense coordinates patch together with the corresponding object features is reprojected to the image space to build a cost volume in a joint semantic and geometric error manner.
Temporal Point Cloud Completion with Pose Disturbance
With the help of gated recovery units(GRU) and attention mechanisms as temporal units, we propose a point cloud completion framework that accepts a sequence of unaligned and sparse inputs, and outputs consistent and aligned point clouds.
Geometry-based Distance Decomposition for Monocular 3D Object Detection
The experimental results show that our method achieves the state-of-the-art performance on the monocular 3D Object Detection and Birds Eye View tasks of the KITTI dataset, and can generalize to images with different camera intrinsics.
Ranked #10 on
Monocular 3D Object Detection
on KITTI Cars Moderate
Stereo R-CNN based 3D Object Detection for Autonomous Driving
Our method, called Stereo R-CNN, extends Faster R-CNN for stereo inputs to simultaneously detect and associate object in left and right images.
Multi-View 3D Object Detection Network for Autonomous Driving
We encode the sparse 3D point cloud with a compact multi-view representation.
Edge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection
In this paper, we propose a novel edge preserving and multi-scale contextual neural network for salient object detection.
3D Object Proposals using Stereo Imagery for Accurate Object Class Detection
We then exploit a CNN on top of these proposals to perform object detection.
Monocular 3D Object Detection for Autonomous Driving
The focus of this paper is on proposal generation.
Ranked #8 on
Vehicle Pose Estimation
on KITTI Cars Hard
3D Object Proposals for Accurate Object Class Detection
The goal of this paper is to generate high-quality 3D object proposals in the context of autonomous driving.
Ranked #10 on
Vehicle Pose Estimation
on KITTI Cars Hard
Improving Object Proposals With Multi-Thresholding Straddling Expansion
Based on the characteristics of superpixel tightness distribution, we propose an effective method, namely multi-thresholding straddling expansion (MTSE) to reduce localization bias via fast diversification.
