2D Object Detection
84 papers with code • 14 benchmarks • 59 datasets
Benchmarks
These leaderboards are used to track progress in 2D Object Detection
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Libraries
Use these libraries to find 2D Object Detection models and implementationsDatasets
BDD100K
VisDrone
Hypersim
COCO-O
ExDark
Clear Weather
KITTI MOTS
FlickrLogos-32
RADIATE
PACO
Subtasks
Latest papers with no code
PointSee: Image Enhances Point Cloud
There is a trend to fuse multi-modal information for 3D object detection (3OD).
MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving
Inspired by these approaches on 2D object detection and an approach for multi-view 3D object detection DETR3D, we propose MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer architecture to fuse image and LiDAR features to improve the detection accuracy.
Identifying Out-of-Distribution Samples in Real-Time for Safety-Critical 2D Object Detection with Margin Entropy Loss
Convolutional Neural Networks (CNNs) are nowadays often employed in vision-based perception stacks for safetycritical applications such as autonomous driving or Unmanned Aerial Vehicles (UAVs).
Level Set-Based Camera Pose Estimation From Multiple 2D/3D Ellipse-Ellipsoid Correspondences
In this paper, we propose an object-based camera pose estimation from a single RGB image and a pre-built map of objects, represented with ellipsoidal models.
DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning
In this paper, we propose a multi-objective camera ISP framework that utilizes Deep Reinforcement Learning (DRL) and camera ISP toolbox that consist of network-based and conventional ISP tools.
Delving into the Pre-training Paradigm of Monocular 3D Object Detection
(2) Combining depth estimation and 2D object detection is a promising M3OD pre-training baseline.
A Fingerprint Detection Method by Fingerprint Ridge Orientation Check
Fingerprints are popular among the biometric based systems due to ease of acquisition, uniqueness and availability.
Exploiting Temporal Relations on Radar Perception for Autonomous Driving
We consider the object recognition problem in autonomous driving using automotive radar sensors.
On Hyperbolic Embeddings in 2D Object Detection
Object detection, for the most part, has been formulated in the euclidean space, where euclidean or spherical geodesic distances measure the similarity of an image region to an object class prototype.
ECG classification algorithm based on feature synthetic input and multi-resolution neural networks
With the smart mobile devices as the carrier, high-performance inter-patient and patient-specific real-time ECG classification methods based on Convolutional Neural Network (CNN) are proposed, which focus on solving the problems of high complexity of data preprocessing and low detection accuracy of arrhythmia.
