Papers with Code 아카이브

Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/czy341181/AerialDet_error_analysis

TIDE: A General Toolbox for Identifying Object Detection Errors

https://github.com/d-li14/SAN

MutualNet: Adaptive ConvNet via Mutual Learning from Network Width and Resolution

https://github.com/d-li14/mobilenetv2.pytorch

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/d-li14/mobilenetv3.pytorch

Searching for MobileNetV3

https://github.com/d-shivam/Pose-estimation-based-action-recognition-for-help-Situation-Identification

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/d4vidbiertmpl/Solving-Visual-Object-Ambiguities-when-Pointing

Solving Visual Object Ambiguities when Pointing: An Unsupervised Learning Approach

https://github.com/dC4rlos/TFM

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

https://github.com/da-steve101/binary_connect_cifar

Ternary Weight Networks

https://github.com/dacon-ai/K-fashion-baseline

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/dacostaHugo/Adversarial_attacks

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/dafanghe/Tensorflow_SceneText_Oriented_Box_Predictor

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/daheyinyin/ICNet

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

https://github.com/dahliau/DPDist

PCRNet: Point Cloud Registration Network using PointNet Encoding

https://github.com/daijifeng001/MNC

Instance-aware Semantic Segmentation via Multi-task Network Cascades

https://github.com/dajes/DensePose-TorchScript

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/dali92002/htrbymatching

A Few-shot Learning Approach for Historical Ciphered Manuscript Recognition

https://github.com/damien911224/theWorldInSafety

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/dangWV/yolov3_darknet53

YOLOv3: An Incremental Improvement

https://github.com/daniel-cores/SLTnet

https://github.com/danielamassiceti/CCA-visualdialogue

Deep Residual Learning for Image Recognition

https://github.com/danielbis/python_cheap_fashion

Going Deeper with Convolutions

https://github.com/danielenricocahall/Keras-UNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/danielgordon10/vince

Self-Supervised Learning of Pretext-Invariant Representations

https://github.com/danielparada1/RL_SpaceInvaders

Deep Residual Learning for Image Recognition

https://github.com/danielpatrickhug/Research_Paper_Parser

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/danielzgsilva/MOT

Tracking Objects as Points

https://github.com/danijorgesantos/detectcars

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/danilojodas/MobileNet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/dannofield/CarND-Extended-Kalman-Filter

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/darkAlert/yolov3-rt

YOLOv3: An Incremental Improvement

https://github.com/darshans0200/YOLOTest

YOLO9000: Better, Faster, Stronger

https://github.com/darya-baranovskaya/keyword_spotting

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/datoboat/Vehicle-Detection

Deep Residual Learning for Image Recognition

https://github.com/daveboat/pytorch_focal_loss

Focal Loss for Dense Object Detection

https://github.com/daveboat/spp

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

https://github.com/david8862/keras-YOLOv3-model-set

YOLOv4: Optimal Speed and Accuracy of Object Detection

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