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/greatsharma/DeepLearning-Papers-Implementation

Going Deeper with Convolutions

https://github.com/greenwaves-technologies/image_classification_networks

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/gregbugaj/unet-reference-impl

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/gregor-ge/mblip

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

https://github.com/griffbr/ODMS

Depth from Camera Motion and Object Detection

https://github.com/griffbr/VOSVS

Mobile Robot Manipulation using Pure Object Detection

https://github.com/grifon-239/diploma

YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection

https://github.com/gsan2/FairMOT

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

https://github.com/gswycf/signgraph

Vision GNN: An Image is Worth Graph of Nodes

https://github.com/guagen/yolov3-ultralytics-source

YOLOv3: An Incremental Improvement

https://github.com/guanfuchen/Deformable-ConvNets

R-FCN: Object Detection via Region-based Fully Convolutional Networks

https://github.com/guanfuchen/py-faster-rcnn

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

https://github.com/guanfuchen/video_obj

Optimizing Video Object Detection via a Scale-Time Lattice

https://github.com/guglielmocamporese/hands-segmentation-pytorch

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/guide2157/ChulaXrayClassifier

Squeeze-and-Excitation Networks

https://github.com/guilherme-pombo/keras_resnext_fpn

Feature Pyramid Networks for Object Detection

https://github.com/guilk/vlc

Masked Autoencoders Are Scalable Vision Learners

https://github.com/guluguluhhhh/contrib/tree/43-1/application/factorized-attention-self-attention-with-linear-complexities

Efficient Attention: Attention with Linear Complexities

https://github.com/gundeep15/SCD_AI_Project

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/gunooknam/Code_Study_Yolov3

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

https://github.com/guohaoyuan/CenterNet-annotation

CenterNet: Keypoint Triplets for Object Detection

https://github.com/gupta-abhay/pytorch-frn

Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks

https://github.com/guptarohit994/ECE285_Graduate_Descent_SSD

SSD: Single Shot MultiBox Detector

https://github.com/gurkirt/AMTNet

SSD: Single Shot MultiBox Detector

https://github.com/gurkirt/realtime-action-detection

SSD: Single Shot MultiBox Detector

https://github.com/guxiaowei1/yolov3--detection-of-rmb-code-region

YOLOv3: An Incremental Improvement

https://github.com/gvtulder/elasticdeform

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/gyes00205/waymo_tf_object_detection

Focal Loss for Dense Object Detection

https://github.com/gzerveas/gaila_object_detection

Objects as Points

https://github.com/gzw820/PyTorch_YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/hSDB-instrument/hsdb-mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/hackthecrisis2020/sat-images

Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic

https://github.com/hades12580/centermask2

CenterMask : Real-Time Anchor-Free Instance Segmentation

https://github.com/hades12580/solov2_mmdet

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/hady1011/wavenet-c

FcaNet: Frequency Channel Attention Networks

https://github.com/hahahappyboy/GANForCartoon

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

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