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/kaist-cvml/part-clipseg

Open-Vocabulary DETR with Conditional Matching

https://github.com/kakaobrain/scrl

Spatially Consistent Representation Learning

https://github.com/kakaoenterprise/Learning-Debiased-Disentangled

RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening

https://github.com/kaland313/vitmav45-ShipSeakers

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kalelpark/FG-SSL

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

https://github.com/kalelpark/ral

Focal Loss for Dense Object Detection

https://github.com/kalubin-awym/GIoU-loss-for-RetinaNet

Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

https://github.com/kalviny/IMTA

Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges

https://github.com/kamanphoebe/motiondetection

Deep Residual Learning for Image Recognition

https://github.com/kamwoh/Car-Model-Classification

YOLO9000: Better, Faster, Stronger

https://github.com/kanesoban/ssd

SSD: Single Shot MultiBox Detector

https://github.com/kangyiS/caffe_ky

SSD: Single Shot MultiBox Detector

https://github.com/kannyjyk/Nested-UNet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/karan96/NewOne

YOLO9000: Better, Faster, Stronger

https://github.com/kargarisaac/3d-MNIST-classification-PointNet

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/kargarisaac/PointNet-SemSeg-VKITTI3D

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

https://github.com/karl1109/scsegamba

PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition

https://github.com/karolzak/keras-unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kaseris/ILSVRCPlus

Going Deeper with Convolutions

https://github.com/katieluo88/280finalproj_nyudepth

Fast Robust Monocular Depth Estimation for Obstacle Detection with Fully Convolutional Networks

https://github.com/kaung-htet-myat/feature-distillation-tf

A Comprehensive Overhaul of Feature Distillation

https://github.com/kaustavsenkvs/Deep-Learning-Mini-Project

YOLOv3: An Incremental Improvement

https://github.com/kav-institute/mdn_trajectory_forecasting

nuScenes: A multimodal dataset for autonomous driving

https://github.com/kawshik8/DL-project

Focal Loss for Dense Object Detection

https://github.com/kazuto1011/pspnet-pytorch

Pyramid Scene Parsing Network

https://github.com/kbardool/mrcnn3

Mask R-CNN

https://github.com/kcang2/Prune_U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kclip/localized-adaptive-risk-control

Deep Residual Learning for Image Recognition

https://github.com/kcmeehan/SmartDetect

RepPoints: Point Set Representation for Object Detection

https://github.com/kdethoor/panoptictorch

Mask R-CNN

https://github.com/kdha0727/cancer-instance-segmentation-from-tissue

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kdha0727/lung-opacity-and-covid-chest-x-ray-detection

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

https://github.com/kdhingra307/temp

Pyramid Scene Parsing Network

https://github.com/kdr/videorag-mrr2024

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

https://github.com/keenborder786/Image-Annotation-Research

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/keevin60907/mp-YOLO

Object Detection in Equirectangular Panorama

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