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/juergenlandauer/Maya-Challenge

Focal Loss for Dense Object Detection

https://github.com/julia-bush/unet_TGS

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/julik43/IIMAS-USCS

Deep Residual Learning for Image Recognition

https://github.com/jun-fang/PWLQ

Post-Training Piecewise Linear Quantization for Deep Neural Networks

https://github.com/jung-jun-uk/mixface

Deep Residual Learning for Image Recognition

https://github.com/junhyukso/SNIP-tf

SNIP: Single-shot Network Pruning based on Connection Sensitivity

https://github.com/junshutang/Make-It-3D

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

https://github.com/juntingzh/incremental-learning-baselines

Class-incremental Learning via Deep Model Consolidation

https://github.com/justinbellucci/cnn-visualizations-pytorch

How convolutional neural network see the world - A survey of convolutional neural network visualization methods

https://github.com/justld/BisNetV1_paddle

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

https://github.com/justld/CCNet_paddle

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/justld/CycleMlp_paddle

CycleMLP: A MLP-like Architecture for Dense Prediction

https://github.com/justld/EspnetV2_paddle

ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network

https://github.com/justld/PVTV2_paddle

PVT v2: Improved Baselines with Pyramid Vision Transformer

https://github.com/jvanvugt/pytorch-unet

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/jvoynow/ConvNet-Architectures

Deep Residual Learning for Image Recognition

https://github.com/jwchoi384/Gaussian_YOLOv3

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving

https://github.com/jwwangchn/AI-TOD

https://github.com/jwwangchn/mmdet-aitod

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/jxhuang0508/RDA

Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection

https://github.com/jxl152/Point-Transformer

Point Transformer

https://github.com/jyhengcoder/Triplet-Attention-tf

Rotate to Attend: Convolutional Triplet Attention Module

https://github.com/jylins/core-text

Mask R-CNN

https://github.com/k-miran/hear

Deep Residual Learning for Image Recognition

https://github.com/k5iogura/darknetAB

YOLO9000: Better, Faster, Stronger

https://github.com/kacerj3/caffe-refinedet

Single-Shot Refinement Neural Network for Object Detection

https://github.com/kadirnar/deepsort-pip

StrongSORT: Make DeepSORT Great Again

https://github.com/kadirnar/ocsort-pip

Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking

https://github.com/kadirnar/yolov5-strongsort

StrongSORT: Make DeepSORT Great Again

https://github.com/kadirnar/yolov6-pip

YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

https://github.com/kadirnar/yolov7-pip

YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

https://github.com/kaichoulyc/course_segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/kaiko-ai/eva

Emerging Properties in Self-Supervised Vision Transformers

https://github.com/kairess/efficientnet_example

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/kaishengtai/neuralart

Going Deeper with Convolutions

https://github.com/kaist-cvml-lab/part-clipseg

Open-Vocabulary DETR with Conditional Matching

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