Papers with Code 아카이브

2D Object Detection

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하위 태스크

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평가표

20

보존된 평가 기록

57

코드

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

https://github.com/Lizhe1228/MambaDFuse

공식 코드

MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusion

https://github.com/LouisYuxuLu/ERANet

공식 코드

Real-Time Multi-Scene Visibility Enhancement for Promoting Navigational Safety of Vessels Under Complex Weather Conditions

https://github.com/LourencoVazPato/seeing-without-looking

공식 코드

Seeing without Looking: Contextual Rescoring of Object Detections for AP Maximization

https://github.com/Lucia-Ningning/Adaptive_Fusion_RGBD_Saliency_Detection

공식 코드

Adaptive Fusion for RGB-D Salient Object Detection

https://github.com/Lucs1590/Coffee_Recognize

공식 코드

Artificial intelligence for detection and quantification of rust and leaf miner in coffee crop

https://github.com/Lx-Bao/QSFNet

공식 코드

Quality-aware Selective Fusion Network for V-D-T Salient Object Detection

https://github.com/M4gicT0/autonomous-drone-racing

공식 코드

Image Generation for Efficient Neural Network Training in Autonomous Drone Racing

https://github.com/MCG-NJU/MOTIP

공식 코드

Multiple Object Tracking as ID Prediction

https://github.com/MECLabTUDA/VoxelSceneGraph

공식 코드

Voxel Scene Graph for Intracranial Hemorrhage

https://github.com/MIC-DKFZ/nnDetection

공식 코드

nnDetection: A Self-configuring Method for Medical Object Detection

https://github.com/MIPT-Oulu/DeepWrist

공식 코드

Critical Evaluation of Deep Neural Networks for Wrist Fracture Detection

https://github.com/MIT-HAN-LAB/temporal-shift-module

공식 코드

TSM: Temporal Shift Module for Efficient Video Understanding

https://github.com/MIT-SPARK/TEASER-plusplus

공식 코드

TEASER: Fast and Certifiable Point Cloud Registration

https://github.com/MMehdiMousavi/SuperCaustics

공식 코드

SuperCaustics: Real-time, open-source simulation of transparent objects for deep learning applications

https://github.com/Madave94/multi-annotator-toolkit

공식 코드

Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations

https://github.com/MadryLab/cifar10_challenge

공식 코드

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/MadryLab/mnist_challenge

공식 코드

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/MahmudulHasan11085/Vision-Eagle-Attention

공식 코드

Vision Eagle Attention: a new lens for advancing image classification

https://github.com/MahyarNajibi/SNIPER

공식 코드

SNIPER: Efficient Multi-Scale Training

https://github.com/MalongTech/research-fad

공식 코드

Representation Sharing for Fast Object Detector Search and Beyond

https://github.com/Manjuphoenix/IndraEye

공식 코드

IndraEye: Infrared Electro-Optical UAV-based Perception Dataset for Robust Downstream Tasks

https://github.com/MartinHahner/LiDAR_fog_sim

공식 코드

Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather

https://github.com/MasterBin-IIAU/UNINEXT

공식 코드

Universal Instance Perception as Object Discovery and Retrieval

https://github.com/MasterHow/CoBEV

공식 코드

CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementarity

https://github.com/MathLee/CMWNet

공식 코드

Cross-Modal Weighting Network for RGB-D Salient Object Detection

https://github.com/MathLee/ICNet-for-RGBD-SOD

공식 코드

RGB-D Salient Object Detection: A Survey

https://github.com/Mazin-Hnewa/MS-DAYOLO

공식 코드

Multiscale Domain Adaptive YOLO for Cross-Domain Object Detection

https://github.com/MedChaabane/DEFT

공식 코드

DEFT: Detection Embeddings for Tracking

https://github.com/Media-Smart/vedadet/tree/main/configs/trainval/tinaface

공식 코드

TinaFace: Strong but Simple Baseline for Face Detection

https://github.com/Megvii-BaseDetection/AutoAssign

공식 코드

AutoAssign: Differentiable Label Assignment for Dense Object Detection

https://github.com/Megvii-BaseDetection/BorderDet

공식 코드

BorderDet: Border Feature for Dense Object Detection

https://github.com/Megvii-BaseDetection/DeFCN

공식 코드

End-to-End Object Detection with Fully Convolutional Network

https://github.com/Megvii-BaseDetection/DisAlign

공식 코드

Distribution Alignment: A Unified Framework for Long-tail Visual Recognition

https://github.com/Megvii-BaseDetection/GFSD

공식 코드

Generalized Few-Shot Object Detection without Forgetting

https://github.com/Megvii-BaseDetection/LLA

공식 코드

LLA: Loss-aware Label Assignment for Dense Pedestrian Detection

https://github.com/Megvii-BaseDetection/OTA

공식 코드

OTA: Optimal Transport Assignment for Object Detection

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