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/meituan/yolov6

공식 코드

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

https://github.com/mendelxu/mixtraining

공식 코드

Bootstrap Your Object Detector via Mixed Training

https://github.com/mendelxu/zsseg.baseline

공식 코드

A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model

https://github.com/mengkesong/saliency-ranking-paradigm

공식 코드

Rethinking Object Saliency Ranking: A Novel Whole-flow Processing Paradigm

https://github.com/mengqidyangge/hierkd

공식 코드

Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation

https://github.com/mengtan00/geobev

공식 코드

GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object Detection

https://github.com/mengtan00/sa-bev

공식 코드

SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection

https://github.com/mengyangpu/edter

공식 코드

EDTER: Edge Detection with Transformer

https://github.com/mengyuwang826/segrefiner

공식 코드

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

https://github.com/menoly-xin/hardness-level-learning

공식 코드

Not All Pixels Are Equal: Learning Pixel Hardness for Semantic Segmentation

https://github.com/merlresearch/radar-detection-transformer

공식 코드

RETR: Multi-View Radar Detection Transformer for Indoor Perception

https://github.com/mertalbaba/SyNet

공식 코드

SyNet: An Ensemble Network for Object Detection in UAV Images

https://github.com/mertseker-dev/social-distance-estimation

공식 코드

Automatic Social Distance Estimation From Images: Performance Evaluation, Test Benchmark, and Algorithm

https://github.com/meteahishali/CSENDistance

공식 코드

Representation Based Regression for Object Distance Estimation

https://github.com/meteoswiss/c4dl-lightningdl

공식 코드

Seamless lightning nowcasting with recurrent-convolutional deep learning

https://github.com/metu-kovan/METU-ALET

공식 코드

ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild

https://github.com/mfigurnov/sact

공식 코드

Spatially Adaptive Computation Time for Residual Networks

https://github.com/mgholamikn/ETran

공식 코드

ETran: Energy-Based Transferability Estimation

https://github.com/mi3labucm/coooler

공식 코드

Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety

https://github.com/michaelthoreau/SearchAndRescueNet

공식 코드

SaRNet: A Dataset for Deep Learning Assisted Search and Rescue with Satellite Imagery

https://github.com/mickeykang16/ev3dod

공식 코드

Ev-3DOD: Pushing the Temporal Boundaries of 3D Object Detection with Event Cameras

https://github.com/microndla/mobilevitv3

공식 코드

MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

https://github.com/microsoft/DynamicHead

공식 코드

Dynamic Head: Unifying Object Detection Heads with Attentions

https://github.com/microsoft/Focal-Transformer

공식 코드

Focal Self-attention for Local-Global Interactions in Vision Transformers

https://github.com/microsoft/FocalNet

공식 코드

Focal Modulation Networks

https://github.com/microsoft/GLIP

공식 코드

Grounded Language-Image Pre-training

https://github.com/microsoft/RelationNet2

공식 코드

RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder

https://github.com/microsoft/RepPoints

공식 코드

RepPoints: Point Set Representation for Object Detection

https://github.com/microsoft/SNR

공식 코드

Style Normalization and Restitution for Domain Generalization and Adaptation

https://github.com/microsoft/SPACH

공식 코드

When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism

https://github.com/microsoft/SoftTeacher

공식 코드

End-to-End Semi-Supervised Object Detection with Soft Teacher

https://github.com/microsoft/Swin-Transformer

공식 코드

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

https://github.com/microsoft/YOLaT-VectorGraphicsRecognition

공식 코드

Recognizing Vector Graphics without Rasterization

https://github.com/microsoft/activemlp

공식 코드

Active Token Mixer

https://github.com/microsoft/comphrdoc

공식 코드

Detect-Order-Construct: A Tree Construction based Approach for Hierarchical Document Structure Analysis

https://github.com/microsoft/cream

공식 코드

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

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