Papers with Code 아카이브

Object Detection

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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/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

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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

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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

공식 코드

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

공식 코드

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

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

공식 코드

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

공식 코드

Distilling Knowledge by Mimicking Features

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

공식 코드

Distilling Knowledge by Mimicking Features

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

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Distilling Knowledge by Mimicking Features

https://github.com/Don767/segdet_mlcr2024

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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

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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

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RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning

https://github.com/ENSTA-U2IS-AI/Multimodal_Deep_segmentation

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InfraParis: A multi-modal and multi-task autonomous driving dataset

https://github.com/ENSTA-U2IS-AI/torch-uncertainty

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MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks

https://github.com/EPFL-VILAB/XTConsistency

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Robust Learning Through Cross-Task Consistency

https://github.com/Eaphan/GLENet

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GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation

https://github.com/Eaphan/Robust3DOD

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A Comprehensive Study of the Robustness for LiDAR-based 3D Object Detectors against Adversarial Attacks

https://github.com/Eisbaer8/DeepGTAV

공식 코드

Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles

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