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/lhoangan/multas

공식 코드

Data exploitation: multi-task learning of object detection and semantic segmentation on partially annotated data

https://github.com/lhoyer/mic

공식 코드

MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation

https://github.com/lhy-zjut/cfmw

공식 코드

CFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions

https://github.com/li-qingyun/mllm-mmrotate

공식 코드

A Simple Aerial Detection Baseline of Multimodal Language Models

https://github.com/li-yachuan/ctfn-pytorch-master

공식 코드

Compact Twice Fusion Network for Edge Detection

https://github.com/li-yachuan/edmb

공식 코드

EDMB: Edge Detector with Mamba

https://github.com/li-yachuan/nbed

공식 코드

A new baseline for edge detection: Make Encoder-Decoder great again

https://github.com/lianqing11/monojsg

공식 코드

MonoJSG: Joint Semantic and Geometric Cost Volume for Monocular 3D Object Detection

https://github.com/libeineu/fairseq_mmt

공식 코드

On Vision Features in Multimodal Machine Translation

https://github.com/libraflower/MutipleFeature-for-PRID

공식 코드

Hybrid-Attention Guided Network with Multiple Resolution Features for Person Re-Identification

https://github.com/libuyu/GHM_Detection

공식 코드

Gradient Harmonized Single-stage Detector

https://github.com/lidar-perception/lidar-cs

공식 코드

LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection

https://github.com/lids-datasets/schistossoma-eggs

공식 코드

FLIM-based Salient Object Detection Networks with Adaptive Decoders

https://github.com/liewfeng/beam

공식 코드

Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection

https://github.com/liewfeng/imted

공식 코드

Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection

https://github.com/liewfeng/raydn

공식 코드

Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection

https://github.com/ligang-cs/PseCo

공식 코드

PseCo: Pseudo Labeling and Consistency Training for Semi-Supervised Object Detection

https://github.com/lightdxy/bootmae

공식 코드

Bootstrapped Masked Autoencoders for Vision BERT Pretraining

https://github.com/liguopeng0923/LGP

공식 코드

Towards Generic and Controllable Attacks Against Object Detection

https://github.com/lijfrank-open/SFCHD-SCALE

공식 코드

Large, Complex, and Realistic Safety Clothing and Helmet Detection: Dataset and Method

https://github.com/liketheflower/simcrosstrans

공식 코드

simCrossTrans: A Simple Cross-Modality Transfer Learning for Object Detection with ConvNets or Vision Transformers

https://github.com/liketheflower/uoddm

공식 코드

Unified Object Detector for Different Modalities based on Vision Transformers

https://github.com/likojack/odam

공식 코드

ODAM: Object Detection, Association, and Mapping using Posed RGB Video

https://github.com/limbo0000/InstanceLoc

공식 코드

Instance Localization for Self-supervised Detection Pretraining

https://github.com/lime-j/lime-eval

공식 코드

LIME-Eval: Rethinking Low-light Image Enhancement Evaluation via Object Detection

https://github.com/liming-ai/AlignDet

공식 코드

AlignDet: Aligning Pre-training and Fine-tuning in Object Detection

https://github.com/linfeng-tang/psfusion

공식 코드

Rethinking the Evaluation of Visible and Infrared Image Fusion

https://github.com/linfeng93/large-unidet

공식 코드

Universal Object Detection with Large Vision Model

https://github.com/lingxiaoli94/pol

공식 코드

Learning Proximal Operators to Discover Multiple Optima

https://github.com/linkon87/exploring-diversity-based-active-learning-for-3d-object-detection-in-autonomous-driving

공식 코드

Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving

https://github.com/linnanwang/AlphaX-NASBench101

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AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search

https://github.com/lintotao/out-of-bbox-attack

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Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors

https://github.com/linusericsson/ssl-transfer

공식 코드

How Well Do Self-Supervised Models Transfer?

https://github.com/linuxsino/senet

공식 코드

A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection

https://github.com/linwei-chen/fadc

공식 코드

Frequency-Adaptive Dilated Convolution for Semantic Segmentation

https://github.com/linwei-chen/fdconv

공식 코드

Frequency Dynamic Convolution for Dense Image Prediction

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