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/human-analysis/MUXConv

공식 코드

MUXConv: Information Multiplexing in Convolutional Neural Networks

https://github.com/humza909/survery-image-mixing-and-deleting-for-data-augmentation

공식 코드

Survey: Image Mixing and Deleting for Data Augmentation

https://github.com/hungntt/LangXAI

공식 코드

LangXAI: Integrating Large Vision Models for Generating Textual Explanations to Enhance Explainability in Visual Perception Tasks

https://github.com/hunterj-lin/activeteacher

공식 코드

Active Teacher for Semi-Supervised Object Detection

https://github.com/hunto/diffkd

공식 코드

Knowledge Diffusion for Distillation

https://github.com/hunto/dist_kd

공식 코드

Knowledge Distillation from A Stronger Teacher

https://github.com/hunto/lightvit

공식 코드

LightViT: Towards Light-Weight Convolution-Free Vision Transformers

https://github.com/hunto/maskd

공식 코드

Masked Distillation with Receptive Tokens

https://github.com/hust-jy/dds3d

공식 코드

DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object Detection

https://github.com/hustgetlijun/RCAN

공식 코드

Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacement

https://github.com/hustvl/LSFA

공식 코드

Real-Time and Accurate Object Detection in Compressed Video by Long Short-term Feature Aggregation

https://github.com/hustvl/MSG-Transformer

공식 코드

MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens

https://github.com/hustvl/QueryInst

공식 코드

Instances as Queries

https://github.com/hustvl/YOLOS

공식 코드

You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection

https://github.com/hustvl/azinorm

공식 코드

AziNorm: Exploiting the Radial Symmetry of Point Cloud for Azimuth-Normalized 3D Perception

https://github.com/hustvl/featurized-queryrcnn

공식 코드

Featurized Query R-CNN

https://github.com/hustvl/mim4d

공식 코드

MIM4D: Masked Modeling with Multi-View Video for Autonomous Driving Representation Learning

https://github.com/hustvl/mimdet

공식 코드

Unleashing Vanilla Vision Transformer with Masked Image Modeling for Object Detection

https://github.com/hustvl/sparseinst

공식 코드

Sparse Instance Activation for Real-Time Instance Segmentation

https://github.com/hustvl/vim

공식 코드

Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

https://github.com/hustvl/weaksam

공식 코드

WeakSAM: Segment Anything Meets Weakly-supervised Instance-level Recognition

https://github.com/hustvl/yolop

공식 코드

YOLOP: You Only Look Once for Panoptic Driving Perception

https://github.com/huuxiaobin/hitnet

공식 코드

High-resolution Iterative Feedback Network for Camouflaged Object Detection

https://github.com/huyvvo/bib

공식 코드

Active Learning Strategies for Weakly-supervised Object Detection

https://github.com/hvision-nku/camoformer

공식 코드

CamoFormer: Masked Separable Attention for Camouflaged Object Detection

https://github.com/hvision-nku/conv2former

공식 코드

Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition

https://github.com/hvxlab/hvdetfusion

공식 코드

HVDetFusion: A Simple and Robust Camera-Radar Fusion Framework

https://github.com/hwang1996/Meta-Concepts-for-Video-Captioning

공식 코드

Cross-Modal Graph with Meta Concepts for Video Captioning

https://github.com/hy0523/mtnet

공식 코드

Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation

https://github.com/hyeon-jo/interchange-transfer-kd

공식 코드

itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection

https://github.com/hyjhkoh/mgtanet

공식 코드

MGTANet: Encoding Sequential LiDAR Points Using Long Short-Term Motion-Guided Temporal Attention for 3D Object Detection

https://github.com/hyunjs/sgt

공식 코드

Detection Recovery in Online Multi-Object Tracking with Sparse Graph Tracker

https://github.com/hyz-xmaster/VarifocalNet

공식 코드

VarifocalNet: An IoU-aware Dense Object Detector

https://github.com/hyz-xmaster/swa_object_detection

공식 코드

SWA Object Detection

https://github.com/hzai-zjnu/mamba-yolo

공식 코드

Mamba YOLO: A Simple Baseline for Object Detection with State Space Model

https://github.com/hzai-zjnu/remdet

공식 코드

RemDet: Rethinking Efficient Model Design for UAV Object Detection

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