Papers with Code 아카이브

2D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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/ShramanPramanick/VoLTA

공식 코드

VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment

https://github.com/ShreyasSkandanS/pst900_thermal_rgb

공식 코드

PST900: RGB-Thermal Calibration, Dataset and Segmentation Network

https://github.com/ShuLiu1993/PANet

공식 코드

Path Aggregation Network for Instance Segmentation

https://github.com/ShuhanChen/PGAR_ECCV20

공식 코드

RGB-D Salient Object Detection: A Survey

https://github.com/Simon-Lepage/LRVSF-Benchmark

공식 코드

LRVS-Fashion: Extending Visual Search with Referring Instructions

https://github.com/Simula-COMPLEX/pure

공식 코드

Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving

https://github.com/Sina-Mohammadi/DFNet

공식 코드

DFNet: Discriminative feature extraction and integration network for salient object detection

https://github.com/Smart-Agri-DIAG/sdg4ad

공식 코드

Synthetic Data Generation for Anomaly Detection on Table Grapes

https://github.com/So-Cool/bLIMEy

공식 코드

LIMEtree: Consistent and Faithful Multi-class Explanations

https://github.com/SoheilaHatami/Face-Mask-Detection

공식 코드

Wearing face mask detection using deep learning through COVID-19 pandemic

https://github.com/Sompote/YOLO9tr

공식 코드

YOLO9tr: A Lightweight Model for Pavement Damage Detection Utilizing a Generalized Efficient Layer Aggregation Network and Attention Mechanism

https://github.com/SonyResearch/RAW-Diffusion

공식 코드

RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation

https://github.com/Star-xing1/SAUGE

공식 코드

SAUGE: Taming SAM for Uncertainty-Aligned Multi-Granularity Edge Detection

https://github.com/StarsThu2016/ApproxDet

공식 코드

ApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles

https://github.com/StevenGrove/DynamicHead

공식 코드

Fine-Grained Dynamic Head for Object Detection

https://github.com/StevenGrove/LearnableTreeFilterV2

공식 코드

Rethinking Learnable Tree Filter for Generic Feature Transform

https://github.com/StiphyJay/FastPillars

공식 코드

FastPillars: A Deployment-friendly Pillar-based 3D Detector

https://github.com/SunYM2020/UA-CMDet

공식 코드

Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning

https://github.com/Sunmi-AI-Lab/head-detection-and-tracking

공식 코드

Towards in-store multi-person tracking using head detection and track heatmaps

https://github.com/SwinTransformer/Feature-Distillation

공식 코드

Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation

https://github.com/SwinTransformer/Transformer-SSL

공식 코드

Self-Supervised Learning with Swin Transformers

https://github.com/SymbioticLab/FedScale

공식 코드

FedScale: Benchmarking Model and System Performance of Federated Learning at Scale

https://github.com/SysCV/bdd100k-models

공식 코드

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

https://github.com/SysCV/qdtrack

공식 코드

Quasi-Dense Similarity Learning for Multiple Object Tracking

https://github.com/TAMU-VITA/UAV-NDFT

공식 코드

Delving into Robust Object Detection from Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach

https://github.com/THU-MIG/yolov10

공식 코드

YOLOv10: Real-Time End-to-End Object Detection

https://github.com/THUrssq/Tianchi04

공식 코드

Sparse Adversarial Attack to Object Detection

https://github.com/TJUMMG/DS-Net

공식 코드

DS-Net: Dynamic Spatiotemporal Network for Video Salient Object Detection

https://github.com/TRAILab/CaDDN

공식 코드

Categorical Depth Distribution Network for Monocular 3D Object Detection

https://github.com/TRI-ML/permatrack

공식 코드

Learning to Track with Object Permanence

https://github.com/TRI-ML/sdflabel

공식 코드

Autolabeling 3D Objects with Differentiable Rendering of SDF Shape Priors

https://github.com/TUI-NICR/ESANet

공식 코드

Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis

https://github.com/TUMFTM/CameraRadarFusionNet

공식 코드

A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detection

https://github.com/TUMFTM/RadarVoxelFusionNet

공식 코드

Radar Voxel Fusion for 3D Object Detection

https://github.com/Tajamul21/Grounded_Teacher

공식 코드

Context Aware Grounded Teacher for Source Free Object Detection

https://github.com/Tencent/tencent-ml-images

공식 코드

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning

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