Papers with Code 아카이브

satellite image super-resolution

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yuanyunshuang/fpv_rcnn

공식 코드

Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous Driving

https://github.com/zijianhu/traffic_density_estimation

공식 코드

Turning Traffic Monitoring Cameras into Intelligent Sensors for Traffic Density Estimation

https://github.com/zillur-av/wrong-way-vehicle-detection

공식 코드

A Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking

https://github.com/DerrickXuNu/OpenCOOD

PIXOR: Real-time 3D Object Detection from Point Clouds

https://github.com/Eisbaer8/DeepGTAV

Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?

https://github.com/Jakaria08/EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/Jakaria08/F-EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/Mandroide/gpasb-nvidia2021-track4

Good Practices and A Strong Baseline for Traffic Anomaly Detection

https://github.com/RaDelft/RaDelft-Dataset

Automatic Labelling & Semantic Segmentation with 4D Radar Tensors

https://github.com/TuSimple/RangeDet

RangeDet:In Defense of Range View for LiDAR-based 3D Object Detection

https://github.com/VisDrone/DroneVehicle

Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning

https://github.com/divyam96/EESRGAN

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

https://github.com/gplast/DroNet

DroNet: Efficient convolutional neural network detector for real-time UAV applications

https://github.com/gplast/DroNet_PyTorch

DroNet: Efficient convolutional neural network detector for real-time UAV applications

https://github.com/jshermeyer/RFSR

The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery

https://github.com/jshermeyer/VDSR4Geo

The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery

https://github.com/matciotola/fast-z-pnn

Pansharpening by convolutional neural networks in the full resolution framework

https://github.com/mcordts/cityscapesScripts

Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle Detection

https://github.com/mileyan/pseudo-LiDAR_e2e

PIXOR: Real-time 3D Object Detection from Point Clouds

https://github.com/rafcy/HarpyTM

Extracting the fundamental diagram from aerial footage

https://github.com/sdkchris/Exercise-Sheet-1

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

https://github.com/tensorflow/models

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

https://github.com/tensorflow/models/tree/master/research/object_detection

Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection

https://github.com/tudelft-iv/occluded_vehicle_acoustic_detection

Hearing What You Cannot See: Acoustic Vehicle Detection Around Corners

https://github.com/ucbdrive/3d-vehicle-tracking

Joint Monocular 3D Vehicle Detection and Tracking

https://github.com/yukitsuji/3D_CNN_tensorflow

3D Fully Convolutional Network for Vehicle Detection in Point Cloud

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.