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코드

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

https://github.com/Chernobyllight/ReDSR

공식 코드

Preserving Full Degradation Details for Blind Image Super-Resolution

https://github.com/ChiCheng123/JointDet

공식 코드

Relational Learning for Joint Head and Human Detection

https://github.com/ChipsGuardian/DualConv

공식 코드

DualConv: Dual Convolutional Kernels for Lightweight Deep Neural Networks

https://github.com/ChisonShang/MeshCompletion

공식 코드

Structure-Aware Completion of Photogrammetric Meshes in Urban Road Environment

https://github.com/ChongjianGE/MetaBEV

공식 코드

MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation

https://github.com/ChrisAllenMing/GPA-detection

공식 코드

Cross-domain Detection via Graph-induced Prototype Alignment

https://github.com/Chrisa142857/PolarNet-GCdet

공식 코드

Cervical Glandular Cell Detection from Whole Slide Image with Out-Of-Distribution Data

https://github.com/ChristianMarzahl/EIPH_WSI

공식 코드

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides

https://github.com/ChunbiaoZhu/PDNet

공식 코드

PDNet: Prior-model Guided Depth-enhanced Network for Salient Object Detection

https://github.com/Cli98/DMNet

공식 코드

Density Map Guided Object Detection in Aerial Images

https://github.com/Cloud-CV/object-proposals

공식 코드

Object-Proposal Evaluation Protocol is 'Gameable'

https://github.com/CodeMonsterPHD/GaTector-A-Unified-Framework-for-Gaze-Object-Prediction

공식 코드

GaTector: A Unified Framework for Gaze Object Prediction

https://github.com/Coding-Rod/crime_detection

공식 코드

Distributed Intelligent Video Surveillance for Early Armed Robbery Detection based on Deep Learning

https://github.com/Computer-Vision-in-the-Wild/Elevater_Toolkit_IC

공식 코드

ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models

https://github.com/CongliangLi/LabelImg3D

공식 코드

Simultaneous Multiple Object Detection and Pose Estimation using 3D Model Infusion with Monocular Vision

https://github.com/CongliangLi/SMOPE-Net

공식 코드

Simultaneous Multiple Object Detection and Pose Estimation using 3D Model Infusion with Monocular Vision

https://github.com/Coolshanlan/DDFH-active-3Ddet

공식 코드

Distribution Discrepancy and Feature Heterogeneity for Active 3D Object Detection

https://github.com/CosmiQ/yolt

공식 코드

You Only Look Twice: Rapid Multi-Scale Object Detection In Satellite Imagery

https://github.com/CuiRuikai/SAM-SOD

공식 코드

Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection

https://github.com/CupidJay/Tobias

공식 코드

A Random CNN Sees Objects: One Inductive Bias of CNN and Its Applications

https://github.com/D0352276/CSL-YOLO

공식 코드

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing

https://github.com/D0352276/SFPN-Synthetic-FPN-for-Object-Detection

공식 코드

SFPN: Synthetic FPN for Object Detection

https://github.com/D3lt4lph4/jpeg_deep

공식 코드

Object Detection in the DCT Domain: is Luminance the Solution?

https://github.com/DLR-RM/AugmentedAutoencoder

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Implicit 3D Orientation Learning for 6D Object Detection from RGB Images

https://github.com/DanceTrack/DanceTrack

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DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion

https://github.com/DataGenResearchTeam/expo_markers

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Detection and Segmentation of Custom Objects using High Distraction Photorealistic Synthetic Data

https://github.com/Dayan-Guan/UaDAN

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Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection

https://github.com/DeLightCMU/CASD

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Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection

https://github.com/DebeshJha/ColonSegNet

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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

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

https://github.com/DeepPathology/CCMCT_Bi_Multinucleated

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

https://github.com/DeepPathology/TUPAC16_AlternativeLabels

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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

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