Papers with Code 아카이브

Object Detection

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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/Alexei95/FasTrCaps

공식 코드

FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks

https://github.com/AlexeyAB/darknet

공식 코드

CSPNet: A New Backbone that can Enhance Learning Capability of CNN

https://github.com/Alibaba-MIIL/ASL

공식 코드

Asymmetric Loss For Multi-Label Classification

https://github.com/AlibabaResearch/efficientteacher

공식 코드

Efficient Teacher: Semi-Supervised Object Detection for YOLOv5

https://github.com/AlifAshrafee/ViT-pytorch-for-Cooking-State-Recognition

공식 코드

Rethinking Cooking State Recognition with Vision Transformers

https://github.com/AlmoonYsl/OPEN

공식 코드

OPEN: Object-wise Position Embedding for Multi-view 3D Object Detection

https://github.com/AlonZolfi/YolOOD

공식 코드

YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection

https://github.com/Amirhosein2c/SegFreeOP

공식 코드

Segmentation-Free Outcome Prediction from Head and Neck Cancer PET/CT Images: Deep Learning-Based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs)

https://github.com/AmirhoseinCh/DynamicPatch

공식 코드

Dynamic Adversarial Attacks on Autonomous Driving Systems

https://github.com/Amirhossein-Nayebi/Nordic-Vehicle-Dataset

공식 코드

Nordic Vehicle Dataset (NVD): Performance of vehicle detectors using newly captured NVD from UAV in different snowy weather conditions

https://github.com/Amshaker/GroupMamba

공식 코드

GroupMamba: Efficient Group-Based Visual State Space Model

https://github.com/AnasIbrahim/image_agnostic_segmentation

공식 코드

DoUnseen: Tuning-Free Class-Adaptive Object Detection of Unseen Objects for Robotic Grasping

https://github.com/Andrew-Qibin/CoordAttention

공식 코드

Coordinate Attention for Efficient Mobile Network Design

https://github.com/Andrew-Qibin/ssdlite-pytorch

공식 코드

Rethinking Bottleneck Structure for Efficient Mobile Network Design

https://github.com/Annbless/ViTAE

공식 코드

ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias

https://github.com/Anon6627/Pruning-PGP

공식 코드

Progressive Gradient Pruning for Classification, Detection and DomainAdaptation

https://github.com/Anymake/DRN_CVPR2020

공식 코드

Dynamic Refinement Network for Oriented and Densely Packed Object Detection

https://github.com/ApolloScapeAuto/dataset-api

공식 코드

CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception

https://github.com/ArminLee/OWOD_Review

공식 코드

Open World Object Detection: A Survey

https://github.com/ArrowLuo/GRACE

공식 코드

GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysis

https://github.com/Ascend-Research/AIO-P

공식 코드

AIO-P: Expanding Neural Performance Predictors Beyond Image Classification

https://github.com/AutoAILab/FusionDepth

공식 코드

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

https://github.com/AutoCompSysLab/DCTNet

공식 코드

A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-View

https://github.com/AutoLab-SAI-SJTU/MambaFusion

공식 코드

MambaFusion: Height-Fidelity Dense Global Fusion for Multi-modal 3D Object Detection

https://github.com/AutoVision-cloud/Deformable-PV-RCNN

공식 코드

Deformable PV-RCNN: Improving 3D Object Detection with Learned Deformations

https://github.com/AutoVision-cloud/SA-Det3D

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SA-Det3D: Self-Attention Based Context-Aware 3D Object Detection

https://github.com/AyanKumarBhunia/Deep-One-Shot-Logo-Retrieval

공식 코드

A Deep One-Shot Network for Query-based Logo Retrieval

https://github.com/Azure/mmlspark

공식 코드

MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales

https://github.com/BICLab/EMS-YOLO

공식 코드

Deep Directly-Trained Spiking Neural Networks for Object Detection

https://github.com/BIT-DA/I2V-GAN

공식 코드

I2V-GAN: Unpaired Infrared-to-Visible Video Translation

https://github.com/BOBrown/JADF-caffe

공식 코드

Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection

https://github.com/BR-IDL/PaddleViT

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Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped Attention

https://github.com/Banconxuan/RTS3D

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RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving

https://github.com/BangguWu/ECANet

공식 코드

ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

https://github.com/BarCodeReader/RCSB-PyTorch

공식 코드

Recursive Contour Saliency Blending Network for Accurate Salient Object Detection

https://github.com/BarCodeReader/SelfReformer

공식 코드

SelfReformer: Self-Refined Network with Transformer for Salient Object Detection

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