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/QingbeiGuo/SG-CNN

공식 코드

Self-grouping Convolutional Neural Networks

https://github.com/QingyongHu/SoTA-Point-Cloud

공식 코드

Deep Learning for 3D Point Clouds: A Survey

https://github.com/Qualcomm-AI-research/delta-distillation

공식 코드

Delta Distillation for Efficient Video Processing

https://github.com/Radar-Camera-Fusion/Awesome-Radar-Camera-Fusion

공식 코드

Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

https://github.com/RalphMao/PatchNet

공식 코드

PatchNet -- Short-range Template Matching for Efficient Video Processing

https://github.com/RalphMao/VMetrics

공식 코드

A Delay Metric for Video Object Detection: What Average Precision Fails to Tell

https://github.com/Rishit-dagli/CPPE-Dataset

공식 코드

CPPE-5: Medical Personal Protective Equipment Dataset

https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection

공식 코드

Radar+RGB Attentive Fusion for Robust Object Detection in Autonomous Vehicles

https://github.com/Robert-Mar/VFA

공식 코드

Voxelized 3D Feature Aggregation for Multiview Detection

https://github.com/Rock-100/MonoDet

공식 코드

Geometry-based Distance Decomposition for Monocular 3D Object Detection

https://github.com/Rokken-lab6/Failure-Analysis-and-Model-Repairment

공식 코드

A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging

https://github.com/Ruiyang-061X/UA3D

공식 코드

Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection

https://github.com/RunpeiDong/DGMS

공식 코드

Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks

https://github.com/RuoyuChen10/CCL-FSOD

공식 코드

Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detection

https://github.com/RyanXLi/OneshotDet

공식 코드

One-Shot Object Detection without Fine-Tuning

https://github.com/SHI-Labs/Convolutional-MLPs

공식 코드

ConvMLP: Hierarchical Convolutional MLPs for Vision

https://github.com/SHI-Labs/Neighborhood-Attention-Transformer

공식 코드

Neighborhood Attention Transformer

https://github.com/SHI-Labs/Pseudo-IoU-for-Anchor-Free-Object-Detection

공식 코드

Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection

https://github.com/SIAnalytics/RHINO

공식 코드

Hausdorff Distance Matching with Adaptive Query Denoising for Rotated Detection Transformer

https://github.com/SJTU-Det/R3Det_Tensorflow

공식 코드

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

https://github.com/SJTU-LuHe/TransVOD

공식 코드

End-to-End Video Object Detection with Spatial-Temporal Transformers

https://github.com/SJTU-Thinklab-Det/DOTA-DOAI

공식 코드

SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing

https://github.com/SJTU-Thinklab-Det/OHDet_Tensorflow

공식 코드

On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited

https://github.com/SJTU-Thinklab-Det/r3det-on-mmdetection

공식 코드

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

https://github.com/SLDGroup/GreedyViG

공식 코드

GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs

https://github.com/SLWZwaard/DMT

공식 코드

Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning

https://github.com/SS47816/AGI-Elo

공식 코드

AGI-Elo: How Far Are We From Mastering A Task?

https://github.com/STVIR/Grid-R-CNN

공식 코드

Grid R-CNN Plus: Faster and Better

https://github.com/SYangDong/tse-t

공식 코드

Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection

https://github.com/Sagarika-Singh-99/indonesian_manhwa_translation

공식 코드

Crossing Language Borders: A Pipeline for Indonesian Manhwa Translation

https://github.com/SaliencyMix/SaliencyMix

공식 코드

SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

https://github.com/Scalsol/RepPointsV2

공식 코드

RepPoints V2: Verification Meets Regression for Object Detection

https://github.com/Scalsol/mega.pytorch

공식 코드

Memory Enhanced Global-Local Aggregation for Video Object Detection

https://github.com/SeanChenxy/TDRN

공식 코드

Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos

https://github.com/SeanChenxy/TSSD-OTA

공식 코드

Temporally Identity-Aware SSD with Attentional LSTM

https://github.com/Sekeh-Lab/FogGuard

공식 코드

FogGuard: guarding YOLO against fog using perceptual loss

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