Papers with Code 아카이브

2D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

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평가표

20

보존된 평가 기록

57

코드

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

https://github.com/Shraddha2013/darknetyolo

YOLO9000: Better, Faster, Stronger

https://github.com/Shraddha2013/darknetyolo3

YOLO9000: Better, Faster, Stronger

https://github.com/Shraddha2013/mydarknetyolo

YOLO9000: Better, Faster, Stronger

https://github.com/Shraddha2013/myfileyolo

YOLO9000: Better, Faster, Stronger

https://github.com/ShreyasArthur/StyleGAN-2-with-Urban-Plans

Efficient Attention: Attention with Linear Complexities

https://github.com/ShrishtiHore/Anomaly-Detection-in-CCTV-Surveillance-Videos

Abnormal Event Detection in Videos using Spatiotemporal Autoencoder

https://github.com/Shuai-Xie/BiSeNet-CCP

BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

https://github.com/Shualite/UBNet

Sliding Line Point Regression for Shape Robust Scene Text Detection

https://github.com/ShubhamShaswat/Overhead-Person-Detection

DPDnet: A Robust People Detector using Deep Learning with an Overhead Depth Camera

https://github.com/Shubhambindal2017/Unoffical-Implementation-of-GRAD-CAM-with-Sanity-Checks

Sanity Checks for Saliency Maps

https://github.com/ShuhanChen/RAS_ECCV18

Reverse Attention for Salient Object Detection

https://github.com/Shulk97/JPEG_detection_INSA_ROUEN_project

Fast object detection in compressed JPEG Images

https://github.com/Shulk97/JPEG_detection_Resnet_SSD

Fast object detection in compressed JPEG Images

https://github.com/Shumway82/U-Net-Segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Shun14/panopticFPN-paddle

Panoptic Feature Pyramid Networks

https://github.com/ShunyuYao/blitznet_instance_segment

BlitzNet: A Real-Time Deep Network for Scene Understanding

https://github.com/SiHaoShen/Convolutional-Neural-Networks

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

https://github.com/SiavashCS/sgan_simple

Efficient Attention: Attention with Linear Complexities

https://github.com/Sidu28/Voxel_att

Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection

https://github.com/SifatMd/Research-Papers

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/SilvioGiancola/TrackingNet-devkit

TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

https://github.com/SilvioGiancola/maskrcnn-benchmark

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

https://github.com/Sim-ai/mmdetection2

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/Simurgh818/UCSF_QBI_Hackathon_ImageSegmentor

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/Singh-sid930/YOLO_pytorch

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

https://github.com/SiriusKY/SceneTextDetector

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/SixQuant/U-Net

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/SkalskiP/make-sense

SSD: Single Shot MultiBox Detector

https://github.com/SkyWa7ch3r/ImageSegmentation

Fast-SCNN: Fast Semantic Segmentation Network

https://github.com/SkyWa7ch3r/SceneSegmentation

Fast-SCNN: Fast Semantic Segmentation Network

https://github.com/Skywalker666666/DynaSLAM_4DVD

DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes

https://github.com/SlongLiu/ASL_reproduce

Asymmetric Loss For Multi-Label Classification

https://github.com/SmallMunich/nutonomy_pointpillars

PointPillars: Fast Encoders for Object Detection from Point Clouds

https://github.com/Smallflyfly/yolov3_ultralytics

YOLOv3: An Incremental Improvement

https://github.com/Smiler-Jin/Yolov4

YOLOv3: An Incremental Improvement

https://github.com/Smiler-Jin/frustum_pointnet

Frustum PointNets for 3D Object Detection from RGB-D Data

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