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/guxiaowei1/yolov3--detection-of-rmb-code-region

YOLOv3: An Incremental Improvement

https://github.com/gvtulder/elasticdeform

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/gy65896/DeepSORVF

Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways

https://github.com/gyes00205/waymo_tf_object_detection

Focal Loss for Dense Object Detection

https://github.com/gzerveas/gaila_object_detection

Objects as Points

https://github.com/gzw820/PyTorch_YOLOv4

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/hSDB-instrument/hsdb-mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/hackthecrisis2020/sat-images

Measuring Human and Economic Activity from Satellite Imagery to Support City-Scale Decision-Making during COVID-19 Pandemic

https://github.com/hades12580/centermask2

CenterMask : Real-Time Anchor-Free Instance Segmentation

https://github.com/hades12580/solov2_mmdet

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/hady1011/wavenet-c

FcaNet: Frequency Channel Attention Networks

https://github.com/hahahappyboy/GANForCartoon

Fully Convolutional Networks for Semantic Segmentation

https://github.com/haithink/myWindowsDarknet

YOLO9000: Better, Faster, Stronger

https://github.com/haiyang-w/git

UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation

https://github.com/hamdaan19/NavGuide

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/hamed-ahangari/Separation-Index-of-convolutional-layers-in-EfficientNet-B0

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/hamidriasat/-Computer-Vision-and-Deep-Learning

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/hamidriasat/BASNet

Boundary-Aware Segmentation Network for Mobile and Web Applications

https://github.com/hamidriasat/Computer-Vision-and-Deep-Learning

You Only Look Once: Unified, Real-Time Object Detection

https://github.com/hampen2929/CenterTrack

Tracking Objects as Points

https://github.com/hamzaMahdi/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/hanfried/hanfried-bookmarks

A ConvNet for the 2020s

https://github.com/hangg7/deformable-kernels

Deformable Convolutional Networks

https://github.com/hanghang177/pedestrian_awareness

YOLOv3: An Incremental Improvement

https://github.com/hangkongbei/mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/hankpark0706/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/hankyul2/maxvit-pytorch

MaxViT: Multi-Axis Vision Transformer

https://github.com/hanoonaR/object-centric-ovd

Open-vocabulary Object Detection via Vision and Language Knowledge Distillation

https://github.com/hanouticelina/deformable-DETR

Deformable DETR: Deformable Transformers for End-to-End Object Detection

https://github.com/haochen593/PCA-Fuse_RGBD_CVPR18

https://github.com/haonanguo/remote-sensing-chatgpt

Deep Residual Learning for Image Recognition

https://github.com/haosulab/ManiSkill-Learn

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

https://github.com/haozheliu-st/point-beyond-class

Points as Queries: Weakly Semi-supervised Object Detection by Points

https://github.com/happinesslz/TANet

TANet: Robust 3D Object Detection from Point Clouds with Triple Attention

https://github.com/happytianhao/tade

DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets

https://github.com/happywu/Sequence-Level-Semantics-Aggregation

Sequence Level Semantics Aggregation for Video Object Detection

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