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/hou-yz/mvdetr

공식 코드

Multiview Detection with Shadow Transformer (and View-Coherent Data Augmentation)

https://github.com/hqjenny/CoDeNet

공식 코드

CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs

https://github.com/hrlblab/CircleNet

공식 코드

Circle Representation for Medical Object Detection

https://github.com/hrlblab/open-eoe

공식 코드

Deep Learning-Based Open Source Toolkit for Eosinophil Detection in Pediatric Eosinophilic Esophagitis

https://github.com/hrlblab/weightedcirclefusion

공식 코드

Weighted Circle Fusion: Ensembling Circle Representation from Different Object Detection Results

https://github.com/hsiangwei0903/Deep-EIoU

공식 코드

Iterative Scale-Up ExpansionIoU and Deep Features Association for Multi-Object Tracking in Sports

https://github.com/hsiangwei0903/SportsMOT

공식 코드

Observation Centric and Central Distance Recovery on Sports Player Tracking

https://github.com/hsouri/battle-of-the-backbones

공식 코드

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks

https://github.com/hszhao/ICNet

공식 코드

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

https://github.com/hszhao/PSPNet

공식 코드

Pyramid Scene Parsing Network

https://github.com/htdt/self-supervised

공식 코드

A Survey on Self-Supervised Representation Learning

https://github.com/htqin/awesome-model-quantization

공식 코드

Binary Neural Networks: A Survey

https://github.com/httle/ars-detr

공식 코드

ARS-DETR: Aspect Ratio-Sensitive Detection Transformer for Aerial Oriented Object Detection

https://github.com/hu64/RN-VID

공식 코드

Road User Detection in Videos

https://github.com/hu64/SpotNet

공식 코드

SpotNet: Self-Attention Multi-Task Network for Object Detection

https://github.com/hu64/ffavod

공식 코드

FFAVOD: Feature Fusion Architecture for Video Object Detection

https://github.com/huaaaliu/rgbx_semantic_segmentation

공식 코드

CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers

https://github.com/huage001/painttransformer

공식 코드

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

https://github.com/huangleiBuaa/IterNorm

공식 코드

Iterative Normalization: Beyond Standardization towards Efficient Whitening

https://github.com/huangyebiaoke/steel-pipe-weld-defect-detection

공식 코드

Deep Learning Based Steel Pipe Weld Defect Detection

https://github.com/huangyh98/advreal

공식 코드

AdvReal: Adversarial Patch Generation Framework with Application to Adversarial Safety Evaluation of Object Detection Systems

https://github.com/huangzhe885/codiff

공식 코드

CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection

https://github.com/huangzhe885/roco

공식 코드

RoCo:Robust Collaborative Perception By Iterative Object Matching and Pose Adjustment

https://github.com/huangzizheng01/shufflemamba

공식 코드

Stochastic Layer-Wise Shuffle: A Good Practice to Improve Vision Mamba Training

https://github.com/huanranchen/AdversarialAttacks

공식 코드

Rethinking Model Ensemble in Transfer-based Adversarial Attacks

https://github.com/huawei-noah/CV-backbones

공식 코드

An Image Patch is a Wave: Phase-Aware Vision MLP

https://github.com/huawei-noah/Efficient-Computing

공식 코드

Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism

https://github.com/huawei-noah/Efficient-Computing/tree/master/Detection/Gold-YOLO

공식 코드

Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism

https://github.com/huawei-noah/efficient-ai-backbones

공식 코드

Vision GNN: An Image is Worth Graph of Nodes

https://github.com/huawei-noah/noah-research/tree/master/TokenFusion

공식 코드

Multimodal Token Fusion for Vision Transformers

https://github.com/huawei-noah/vega

공식 코드

An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization

https://github.com/hucaofighting/frn

공식 코드

Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection

https://github.com/huggingface/pytorch-image-models

공식 코드

DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs

https://github.com/huiminshii/dpnet

공식 코드

DPNet: Dual-Path Network for Real-time Object Detection with Lightweight Attention

https://github.com/hujie-frank/SENet

공식 코드

Squeeze-and-Excitation Networks

https://github.com/hujiecpp/ISTR

공식 코드

ISTR: End-to-End Instance Segmentation with Transformers

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