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/roeez/calcification_detection

Segmenting Microcalcifications in Mammograms and its Applications

https://github.com/rohitgr7/tvmodels

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/rohitgupta24/unet_from_scratch

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/root-master/pose-anomaly-detection

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

https://github.com/rootAkash/vision.ai

Objects as Points

https://github.com/rosinality/fcos-pytorch

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/rowantseng/FUnIE-GAN-PyTorch

Fast Underwater Image Enhancement for Improved Visual Perception

https://github.com/roya90/android-yolo

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

https://github.com/roydenwa/cell-centroid-former

MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

https://github.com/rozendetr/mmdetection_copy

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/rrkotik/dental_lucency_finder

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/rrkotik/k_salt_identification

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/rsreetech/MultiModalSearch

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/rstrudel/segmenter

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

https://github.com/rsy6318/CorrI2P

Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration

https://github.com/rt55u-rgb/yolov3

YOLOv3: An Incremental Improvement

https://github.com/rtanno21609/AdaptiveNeuralTrees

Deep Residual Learning for Image Recognition

https://github.com/rudraina/Face-Verification-And-Validation

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

https://github.com/ruhyadi/YOLO3D

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/ruhyadi/yolo3d-lightning

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/ruipingl/opensu

Collaborative Transformers for Grounded Situation Recognition

https://github.com/ruipingl/skr_pea

Distilling Knowledge via Knowledge Review

https://github.com/ruipingl/transkd

Distilling Knowledge via Knowledge Review

https://github.com/ruixif/Unet_keras

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ruotianluo/iep-ref

CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions

https://github.com/ruotianluo/pytorch-faster-rcnn

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

https://github.com/ruyueshuo/DeepStream_YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/ruyueshuo/YOLOv4_Deployment

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/rwightman/efficientdet-pytorch

EfficientDet: Scalable and Efficient Object Detection

https://github.com/rwightman/efficientnet-jax

Searching for MobileNetV3

https://github.com/rwightman/gen-efficientnet-pytorch

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/rwightman/genmobilenet-pytorch

Searching for MobileNetV3

https://github.com/ry/tensorflow-resnet

Deep Residual Learning for Image Recognition

https://github.com/ryanxingql/powerqe

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/rybread1/lego-minifigure-classification

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/rykov8/ssd_keras

SSD: Single Shot MultiBox Detector

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