Papers with Code 아카이브

2D Object Detection

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전체 기법전체 데이터셋

하위 태스크

15

평가표

20

보존된 평가 기록

57

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/DeLightCMU/CASD

공식 코드

Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection

https://github.com/DebeshJha/ColonSegNet

공식 코드

Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

https://github.com/DebugML/sqrl

공식 코드

Do Machine Learning Models Learn Statistical Rules Inferred from Data?

https://github.com/Deceptrax123/Spurious-Correlation-Mitigation-in-YOLOv5

공식 코드

Autoencoder based approach for the mitigation of spurious correlations

https://github.com/DeepPathology/CCMCTBiMultinucleated

공식 코드

Dataset on Bi- and Multi-Nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors

https://github.com/DeepPathology/CCMCT_Bi_Multinucleated

공식 코드

Dataset on Bi- and Multi-Nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors

https://github.com/DeepPathology/TUPAC16_AlternativeLabels

공식 코드

Are pathologist-defined labels reproducible? Comparison of the TUPAC16 mitotic figure dataset with an alternative set of labels

https://github.com/Deepwise-AILab/ChestX-Det-Dataset

공식 코드

A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentation

https://github.com/DengPingFan/BBS-Net

공식 코드

RGB-D Salient Object Detection: A Survey

https://github.com/DengPingFan/CoEGNet

공식 코드

Re-thinking Co-Salient Object Detection

https://github.com/DengPingFan/D3NetBenchmark

공식 코드

Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks

https://github.com/DengPingFan/PraNet

공식 코드

PraNet: Parallel Reverse Attention Network for Polyp Segmentation

https://github.com/DengPingFan/S-measure

공식 코드

Structure-measure: A New Way to Evaluate Foreground Maps

https://github.com/DengPingFan/SOC-DataAug

공식 코드

Salient Objects in Clutter

https://github.com/DenisTome/DeepPed

공식 코드

Deep convolutional neural networks for pedestrian detection

https://github.com/DequanWang/CoDeNet

공식 코드

Algorithm-hardware Co-design for Deformable Convolution

https://github.com/DerrickXuNu/OpenCOOD

공식 코드

OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication

https://github.com/DerrickXuNu/v2x-vit

공식 코드

V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer

https://github.com/DetectionTeamUCAS/R2CNN-Plus-Plus_Tensorflow

공식 코드

SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects

https://github.com/DexterJZ/eval_driving_safety

공식 코드

Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles

https://github.com/Diamond101010/RMMDF

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Recursive Multi-model Complementary Deep Fusion forRobust Salient Object Detection via Parallel Sub Networks

https://github.com/DingXiaoH/DiverseBranchBlock

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Diverse Branch Block: Building a Convolution as an Inception-like Unit

https://github.com/Dishant-P/S-Extension-patch-Official-research-module

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S-Extension Patch: A simple and efficient way to extend an object detection model

https://github.com/Div99/W-Stereo-Disp

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Wasserstein Distances for Stereo Disparity Estimation

https://github.com/Divadi/MTC_RCNN

공식 코드

Multi-Modality Task Cascade for 3D Object Detection

https://github.com/DoctorKey/LSHFM.detection

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Distilling Knowledge by Mimicking Features

https://github.com/DoctorKey/LSHFM.multiclassification

공식 코드

Distilling Knowledge by Mimicking Features

https://github.com/DoctorKey/LSHFM.singleclassification

공식 코드

Distilling Knowledge by Mimicking Features

https://github.com/Don767/segdet_mlcr2024

공식 코드

Replication Study and Benchmarking of Real-Time Object Detection Models

https://github.com/DongSky/lbba_boosted_wsod

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Boosting Weakly Supervised Object Detection via Learning Bounding Box Adjusters

https://github.com/Duankaiwen/CPNDet

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Corner Proposal Network for Anchor-free, Two-stage Object Detection

https://github.com/Duankaiwen/CenterNet

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CenterNet: Keypoint Triplets for Object Detection

https://github.com/Duankaiwen/LSNet

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Location-Sensitive Visual Recognition with Cross-IOU Loss

https://github.com/Duankaiwen/PyCenterNet

공식 코드

CenterNet++ for Object Detection

https://github.com/Dwrety/mmdetection-selective-iou

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Solving Missing-Annotation Object Detection with Background Recalibration Loss

https://github.com/EMI-Group/RelativeNAS

공식 코드

RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning

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