Papers with Code 아카이브

Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/mileyan/pseudo-LiDAR_e2e

공식 코드

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection

https://github.com/mileyan/pseudo_lidar

공식 코드

Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

https://github.com/mililab/roma

공식 코드

RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing

https://github.com/milinpatel07/SOTIF-PCOD

공식 코드

Uncertainty Representation in a SOTIF-Related Use Case with Dempster-Shafer Theory for LiDAR Sensor-Based Object Detection

https://github.com/miltonbd/ECCV_2018_pedestrian_detection_challenege

공식 코드

Towards Pedestrian Detection Using RetinaNet in ECCV 2018 Wider Pedestrian Detection Challenge

https://github.com/mindgarage-shan/trans_object_detection_survey

공식 코드

Object Detection with Transformers: A Review

https://github.com/mindgarage-shan/transformer_object_detection_survey

공식 코드

Object Detection with Transformers: A Review

https://github.com/mindspore-ai/models/tree/master/research/cv/ISyNet

공식 코드

ISyNet: Convolutional Neural Networks design for AI accelerator

https://github.com/mindspore-ai/models/tree/master/research/cv/TokenFusion

공식 코드

Multimodal Token Fusion for Vision Transformers

https://github.com/mindspore-lab/models

공식 코드

SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization

https://github.com/mindspore-lab/models/tree/master/research/huawei-noah/DECO

공식 코드

DECO: Query-Based End-to-End Object Detection with ConvNets

https://github.com/ming71/CFC-Net

공식 코드

CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images

https://github.com/ming71/DAL

공식 코드

Dynamic Anchor Learning for Arbitrary-Oriented Object Detection

https://github.com/ming71/RIDet

공식 코드

Optimization for Arbitrary-Oriented Object Detection via Representation Invariance Loss

https://github.com/mingbohong/yola

공식 코드

You Only Look Around: Learning Illumination Invariant Feature for Low-light Object Detection

https://github.com/miquel-espinosa/no-time-to-train

공식 코드

No time to train! Training-Free Reference-Based Instance Segmentation

https://github.com/mit-han-lab/bevfusion

공식 코드

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

https://github.com/mit-han-lab/efficientvit

공식 코드

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/mit-han-lab/pvcnn

공식 코드

Point-Voxel CNN for Efficient 3D Deep Learning

https://github.com/mit-han-lab/spvnas

공식 코드

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

https://github.com/mjseong0414/CRT-Fusion

공식 코드

CRT-Fusion: Camera, Radar, Temporal Fusion Using Motion Information for 3D Object Detection

https://github.com/mjseong0414/RCM-Fusion

공식 코드

RCM-Fusion: Radar-Camera Multi-Level Fusion for 3D Object Detection

https://github.com/mk-minchul/attend-and-compare

공식 코드

Learning Visual Context by Comparison

https://github.com/mkang315/CST-YOLO

공식 코드

CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer

https://github.com/mkang315/bgf-yolo

공식 코드

BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection

https://github.com/mkang315/pk-yolo

공식 코드

PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplanar MRI Slices

https://github.com/mkang315/rcs-yolo

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RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection

https://github.com/mkchoi-0323/modified_refinedet

공식 코드

Development of Fast Refinement Detectors on AI Edge Platforms

https://github.com/ml-lab-htw/iterative-annotate

공식 코드

Feedback-driven object detection and iterative model improvement

https://github.com/mlcaepiee/simuav

공식 코드

A Comprehensive Approach for UAV Small Object Detection with Simulation-based Transfer Learning and Adaptive Fusion

https://github.com/mlpc-ucsd/CoaT

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Co-Scale Conv-Attentional Image Transformers

https://github.com/mlvlab/RALF

공식 코드

Retrieval-Augmented Open-Vocabulary Object Detection

https://github.com/mlvlab/cpchoi

공식 코드

Consistency Learning via Decoding Path Augmentation for Transformers in Human Object Interaction Detection

https://github.com/mlvlab/drone_ai_challenge

공식 코드

Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones

https://github.com/mlvlab/drone_task1

공식 코드

Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones

https://github.com/mlvlab/drone_task4

공식 코드

Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones

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