Papers with Code 아카이브

Object Detection

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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/takooctopus/CornerNet-Lite-Tako

CornerNet-Lite: Efficient Keypoint Based Object Detection

https://github.com/takooctopus/Yolov3-Tako

YOLOv3: An Incremental Improvement

https://github.com/tallysprado/myDarknet

YOLO9000: Better, Faster, Stronger

https://github.com/talshaharabany/DeepACM2D

HarDNet: A Low Memory Traffic Network

https://github.com/tamnil/esp32-xtensa-study

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/tancik/fpointnets_image_features

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/tanimutomo/ganonymizer

YOLOv3: An Incremental Improvement

https://github.com/tanjeffreyz/deep-residual-learning

Deep Residual Learning for Image Recognition

https://github.com/tanjeffreyz/yolo-v1

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

https://github.com/tanmayj000/darknet

YOLOv3: An Incremental Improvement

https://github.com/tanmaypandey7/wheat-detection

Dynamic Scale Training for Object Detection

https://github.com/tantara/JejuNet

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/tanyanair/segmentation_uncertainty

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/taokong/RON

SSD: Single Shot MultiBox Detector

https://github.com/taokong/group_normalization

Group Normalization

https://github.com/taranjotsingh01/Car-detection-using-YOLO

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

https://github.com/tarashakhurana/detecting-invisible-people

Detecting Invisible People

https://github.com/tarikdgny/Optical_Coherence_Tomography

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/tarit21/Speech-Enhancement-module

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/tarun-munjal/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/tashchowdhury/FloodNet-Supervised_v1.0

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

https://github.com/tatigabru/kaggle-lyft

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/tatsuyaokunaga/Simpsons_Detection

SSD: Single Shot MultiBox Detector

https://github.com/tattaka/Filter-Response-Normalization-PyTorch

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

https://github.com/tchernitski/caffe.deploy

SSD: Single Shot MultiBox Detector

https://github.com/tcheung99/ResNet_MiniProject

Deep Residual Learning for Image Recognition

https://github.com/tdhock/feature-learning-benchmark

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

https://github.com/tdurand/darknet-withtiling

YOLO9000: Better, Faster, Stronger

https://github.com/tea1528/Non-Local-NN-Pytorch

Non-local Neural Networks

https://github.com/techforgood-kiran/ai

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

https://github.com/teemoeric/projet

YOLO9000: Better, Faster, Stronger

https://github.com/teganmaharaj/movieFIB

A dataset and exploration of models for understanding video data through fill-in-the-blank question-answering

https://github.com/tej-prash/GeneExpression

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

https://github.com/tejaswigowda/semseg-pytorch

Pyramid Scene Parsing Network

https://github.com/tensorboy/centerpose

Objects as Points

https://github.com/tensorflow/addons

Mish: A Self Regularized Non-Monotonic Activation Function

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