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/tkdguraa/point-transformer-tensorflow

Point Transformer

https://github.com/tkhhhh/yolov3-master

YOLOv3: An Incremental Improvement

https://github.com/tkuanlun350/Kaggle_Ship_Detection_2018

Training Region-based Object Detectors with Online Hard Example Mining

https://github.com/tmbaoloc/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/tmoopenn/seq-nms

Seq-NMS for Video Object Detection

https://github.com/tms2003/yolov3

YOLOv3: An Incremental Improvement

https://github.com/toanbkmt/EfficientnetFruitDetect

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/toandaominh1997/EfficientDet.Pytorch

EfficientDet: Scalable and Efficient Object Detection

https://github.com/tolotrasamuel/real-time-object-detection-retraining-ncs-raspberry-pi

SSD: Single Shot MultiBox Detector

https://github.com/tom-roddick/oft

Orthographic Feature Transform for Monocular 3D Object Detection

https://github.com/tommyjtl/darknet-colab

YOLO9000: Better, Faster, Stronger

https://github.com/tonyhsu32/AI-Cafe-with-machine-learning

PVANET: Deep but Lightweight Neural Networks for Real-time Object Detection

https://github.com/tonylins/pytorch-mobilenet-v2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/tonysy/PyAction

Non-local Neural Networks

https://github.com/tonysy/pointnet2_tf

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

https://github.com/tops666/volo-v4-

YOLO9000: Better, Faster, Stronger

https://github.com/toseek01/eyebird

SSD: Single Shot MultiBox Detector

https://github.com/tossy0423/darknet_ros

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

https://github.com/totalgood/viddesc

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

https://github.com/totoadel/Minst

You Only Learn One Representation: Unified Network for Multiple Tasks

https://github.com/touchylk/fcoseccv

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/toufiksk/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/towhee-io/towhee

Deep Residual Learning for Image Recognition

https://github.com/towhee-io/towhee/tree/main/towhee/models/coformer

Collaborative Transformers for Grounded Situation Recognition

https://github.com/towhee-io/towhee/tree/main/towhee/models/tsm

TSM: Temporal Shift Module for Efficient Video Understanding

https://github.com/trachpro/arcface-tf2

Deep Residual Learning for Image Recognition

https://github.com/transcendent-ai-labs/dynaml

Going Deeper with Convolutions

https://github.com/traveller59/second.pytorch

nuScenes: A multimodal dataset for autonomous driving

https://github.com/travismyers19/Vulnerable_Buildings

Focal Loss for Dense Object Detection

https://github.com/trhgu/awesome-fashion-contents

How To Extract Fashion Trends From Social Media? A Robust Object Detector With Support For Unsupervised Learning

https://github.com/trhieu310/customDataset

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/trichtu/ConvLSTM-RAU-net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/trichtu/Recurrent_Attention_U_net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/tripathiarpan20/us-transporter-eval

Domain Specific Transporter Framework to Detect Fractures in Ultrasound

https://github.com/triple7/Keras-WGAN-RGB-128x128

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/trisha-c-a/Visual-Question-Answering-with-Keras

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

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