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/megvii-research/basecls/tree/main/zoo/public/effnet

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/megvii-research/basecls/tree/main/zoo/public/hrnet

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/megvii-research/basecls/tree/main/zoo/public/mbnet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/megvii-research/basecls/tree/main/zoo/public/resnet

Deep Residual Learning for Image Recognition

https://github.com/megvii-research/basecls/tree/main/zoo/public/snet

ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design

https://github.com/megvii-research/basecls/tree/main/zoo/public/swin

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

https://github.com/megvii-research/caddm

SSD: Single Shot MultiBox Detector

https://github.com/megvii-research/fsce

Frustratingly Simple Few-Shot Object Detection

https://github.com/mehrdad-noori/brain-tumor-segmentation

Squeeze-and-Excitation Networks

https://github.com/meijieru/yet_another_mobilenet_series

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/melissande/dhi-segmentation-buildings

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/membrai/deblurringmim

ConvMAE: Masked Convolution Meets Masked Autoencoders

https://github.com/memoatwit/universalperturbation

Gaussian Splatting Under Attack: Investigating Adversarial Noise in 3D Objects

https://github.com/mengfu188/mmdetection.bak

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/mengyingfei/faster-rcnn-tf

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

https://github.com/mergarsal/FastCertRelPose

TEASER: Fast and Certifiable Point Cloud Registration

https://github.com/mertyg/post-hoc-cbm

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/meryusha/seeds_faster

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

https://github.com/metaphorz/deep-image-prior-hqskipnet

Deformable Convolutional Networks

https://github.com/meteahishali/srl-soa

Representation Based Regression for Object Distance Estimation

https://github.com/meteorshowers/X-StereoLab

PLUMENet: Efficient 3D Object Detection from Stereo Images

https://github.com/mf1024/Contrastive-Predictive-Coding-for-Image-Recognition-in-PyTorch

Data-Efficient Image Recognition with Contrastive Predictive Coding

https://github.com/mfp0610/semantic-segmentaion

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/mg2033/shufflenet

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

https://github.com/mgolnezhad/openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/mhagiwara/nanigonet

Deep Residual Learning for Image Recognition

https://github.com/mhernan88/od-toolbelt

ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors

https://github.com/mhorton19/CNN-Kernel-Attention

Squeeze-and-Excitation Networks

https://github.com/mhw32/contrastive-ring-public

Conditional Negative Sampling for Contrastive Learning of Visual Representations

https://github.com/mi-lad/snip

SNIP: Single-shot Network Pruning based on Connection Sensitivity

https://github.com/mialbro/PointFusion

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation

https://github.com/mialbro/pytorch_pointfusion

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation

https://github.com/miaohua1982/simple_fasterrcnn_pytorch

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

https://github.com/mic-dkfz/medicaldetectiontoolkit

Mask R-CNN

https://github.com/michaelisc/cluttered-omniglot

One-Shot Instance Segmentation

https://github.com/michhar/azureml-keras-yolov3-custom

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

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