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/zhanghx-iim-ahu/circleformer

공식 코드

CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention

https://github.com/zhanglab-deepneurocoglab/csegg

공식 코드

Adaptive Visual Scene Understanding: Incremental Scene Graph Generation

https://github.com/zhanglu-cst/hifsod

공식 코드

Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method

https://github.com/zhangtong1/transfer_learning_cspt

공식 코드

Consecutive Pretraining: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain

https://github.com/zhangtravis/hist-da

공식 코드

Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features

https://github.com/zhangxiaosong18/FreeAnchor

공식 코드

FreeAnchor: Learning to Match Anchors for Visual Object Detection

https://github.com/zhangxuying1004/refcod

공식 코드

Referring Camouflaged Object Detection

https://github.com/zhangyp15/MonoFlex

공식 코드

Objects are Different: Flexible Monocular 3D Object Detection

https://github.com/zhangyp15/beverse

공식 코드

BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

https://github.com/zhangyp15/simmod

공식 코드

A Simple Baseline for Multi-Camera 3D Object Detection

https://github.com/zhangyuanhan-ai/bamboo

공식 코드

Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy

https://github.com/zhangzjn/ader

공식 코드

Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark

https://github.com/zhangzjn/emov2

공식 코드

EMOv2: Pushing 5M Vision Model Frontier

https://github.com/zhanyang-nwpu/mono3dvg

공식 코드

Mono3DVG: 3D Visual Grounding in Monocular Images

https://github.com/zhaoweicai/Detectron-Cascade-RCNN

공식 코드

Cascade R-CNN: High Quality Object Detection and Instance Segmentation

https://github.com/zhaoweicai/cascade-rcnn

공식 코드

Cascade R-CNN: Delving into High Quality Object Detection

https://github.com/zhaoweicai/mscnn

공식 코드

A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

https://github.com/zhaoxiangyun/morphable-detector

공식 코드

Morphable Detector for Object Detection on Demand

https://github.com/zhaoxing2022/mmn-vsod

공식 코드

Motion-aware Memory Network for Fast Video Salient Object Detection

https://github.com/zhaoxuli123/specdetr

공식 코드

SpecDETR: A Transformer-based Hyperspectral Point Object Detection Network

https://github.com/zhaozixiang1228/mmif-cddfuse

공식 코드

CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion

https://github.com/zhasion/rsar

공식 코드

RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark

https://github.com/zhechen/deformable-detr-rego

공식 코드

Recurrent Glimpse-based Decoder for Detection with Transformer

https://github.com/zhen6618/rotayolo

공식 코드

Linear Gaussian Bounding Box Representation and Ring-Shaped Rotated Convolution for Oriented Object Detection

https://github.com/zhengbo-zhang/fade

공식 코드

FADE: A Dataset for Detecting Falling Objects around Buildings in Video

https://github.com/zhengpeng7/birefnet

공식 코드

Bilateral Reference for High-Resolution Dichotomous Image Segmentation

https://github.com/zhengpeng7/cosod_fps_collection

공식 코드

GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector

https://github.com/zhengpeng7/gconet_plus

공식 코드

GCoNet+: A Stronger Group Collaborative Co-Salient Object Detector

https://github.com/zhengpeng7/mccl

공식 코드

Memory-aided Contrastive Consensus Learning for Co-salient Object Detection

https://github.com/zhengshuchen/hcfnet

공식 코드

HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection

https://github.com/zhengye1995/BLC

공식 코드

Background Learnable Cascade for Zero-Shot Object Detection

https://github.com/zhengye1995/Zero-shot-Instance-Segmentation

공식 코드

Zero-Shot Instance Segmentation

https://github.com/zhenyuw16/uni3detr

공식 코드

Uni3DETR: Unified 3D Detection Transformer

https://github.com/zhenyuw16/unidetector

공식 코드

Detecting Everything in the Open World: Towards Universal Object Detection

https://github.com/zhh6425/LocalContextPropagation

공식 코드

LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers

https://github.com/zhichenghuang/cmae

공식 코드

Contrastive Masked Autoencoders are Stronger Vision Learners

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