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Found 10 papers, 6 papers with code
Improvement of Frequency Source Phase Noise Reduction Design under Vibration Condition
Reasonable vibration reduction design is an important way to achieve low phase noise index of airborne frequency source output signal.
UniVision: A Unified Framework for Vision-Centric 3D Perception
The past few years have witnessed the rapid development of vision-centric 3D perception in autonomous driving.
MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving
We propose a multi-modal 3D semantic segmentation model (MSeg3D) with joint intra-modal feature extraction and inter-modal feature fusion to mitigate the modality heterogeneity.
Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection
Leveraging LiDAR-based detectors or real LiDAR point data to guide monocular 3D detection has brought significant improvement, e. g., Pseudo-LiDAR methods.
Ranked #1 on
Monocular 3D Object Detection
on KITTI Cyclist Hard
(using extra training data)
Pseudo-Stereo for Monocular 3D Object Detection in Autonomous Driving
Motivated by this, we propose a Pseudo-Stereo 3D detection framework with three novel virtual view generation methods, including image-level generation, feature-level generation, and feature-clone, for detecting 3D objects from a single image.
Ranked #1 on
Monocular 3D Object Detection
on KITTI Cars Moderate
(AP metric)
Perlin Noise Improve Adversarial Robustness
Combined with the defensive idea of adversarial training, we use Perlin noise to train the neural network to obtain a model that can defend against procedural noise adversarial examples.
From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder
In this paper, we present an Intersection-over-Union (IoU) guided two-stage 3D object detector with a voxel-to-point decoder.
Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud
We propose an attentive module to fit the sparse feature maps to dense mostly on the object regions through the deformable convolution tower and the supervised mask-guided attention.
M3DSSD: Monocular 3D Single Stage Object Detector
In the first step, the shape alignment is performed to enable the receptive field of the feature map to focus on the pre-defined anchors with high confidence scores.
3D IoU-Net: IoU Guided 3D Object Detector for Point Clouds
In order to obtain a more accurate IoU prediction, we propose a 3D IoU-Net with IoU sensitive feature learning and an IoU alignment operation.
