Computer Vision
 
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3D Object Detection

582 papers with code • 55 benchmarks • 48 datasets

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.

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Multimodal Token Fusion for Vision Transformers

huawei-noah/noah-research • • journal 2022

Many adaptations of transformers have emerged to address the single-modal vision tasks, where self-attention modules are stacked to handle input sources like images.

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Complex-YOLO: Real-time 3D Object Detection on Point Clouds

maudzung/Complex-YOLOv4-Pytorch • • 16 Mar 2018

We introduce Complex-YOLO, a state of the art real-time 3D object detection network on point clouds only.

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Exploring Data Augmentation for Multi-Modality 3D Object Detection

open-mmlab/mmdetection3d • • 23 Dec 2020

Due to the fact that multi-modality data augmentation must maintain consistency between point cloud and images, recent methods in this field typically use relatively insufficient data augmentation.

8
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FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection

open-mmlab/mmdetection3d • • 22 Apr 2021

In this paper, we study this problem with a practice built on a fully convolutional single-stage detector and propose a general framework FCOS3D.

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PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions

frgfm/Holocron • • ICLR 2022

Cross-entropy loss and focal loss are the most common choices when training deep neural networks for classification problems.

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From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

sshaoshuai/PointCloudDet3D • • 8 Jul 2019

3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications.

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AFDet: Anchor Free One Stage 3D Object Detection

CarkusL/CenterPoint • • 23 Jun 2020

High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving.

6
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Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

mit-han-lab/spvnas • • ECCV 2020

Self-driving cars need to understand 3D scenes efficiently and accurately in order to drive safely.

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CubeSLAM: Monocular 3D Object SLAM

shichaoy/cube_slam • 1 Jun 2018

Objects can provide long-range geometric and scale constraints to improve camera pose estimation and reduce monocular drift.

5
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Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection

open-mmlab/OpenPCDet • • 31 Dec 2020

In this paper, we take a slightly different viewpoint -- we find that precise positioning of raw points is not essential for high performance 3D object detection and that the coarse voxel granularity can also offer sufficient detection accuracy.

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