Papers with Code 아카이브

2D Object Detection

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전체 기법전체 데이터셋

하위 태스크

15

평가표

20

보존된 평가 기록

57

코드

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

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

https://github.com/Bartzi/loans

공식 코드

LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks

https://github.com/BathVisArtData/PeopleArt

공식 코드

Detecting People in Artwork with CNNs

https://github.com/Bedrettin-Cetinkaya/RankED

공식 코드

RankED: Addressing Imbalance and Uncertainty in Edge Detection Using Ranking-based Losses

https://github.com/Benzlxs/tDBN

공식 코드

Three-dimensional Backbone Network for 3D Object Detection in Traffic Scenes

https://github.com/BichenWuUCB/squeezeDet

공식 코드

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

https://github.com/Bissmella/Small-object-detection-transformers

공식 코드

Multimodal Transformer Using Cross-Channel attention for Object Detection in Remote Sensing Images

https://github.com/BoPang1996/TubeTK

공식 코드

TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model

https://github.com/Bob-cheng/MDE_Attack

공식 코드

Physical Attack on Monocular Depth Estimation with Optimal Adversarial Patches

https://github.com/Boese0601/2021-National-Underwater-Robotics-Vision-Optics

공식 코드

CDNet is all you need: Cascade DCN based underwater object detection RCNN

https://github.com/Bohao-Lee/CME

공식 코드

Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection

https://github.com/Boshrakh/Yolov8-Small-Object-Detection-Arial-Images

공식 코드

SOD-YOLOv8 -- Enhancing YOLOv8 for Small Object Detection in Traffic Scenes

https://github.com/Breakend/TemporalYolo

공식 코드

Underwater Multi-Robot Convoying using Visual Tracking by Detection

https://github.com/BrunoSauvalle/AST

공식 코드

Unsupervised Multi-object Segmentation Using Attention and Soft-argmax

https://github.com/BryanPlummer/phrase_detection

공식 코드

Revisiting Image-Language Networks for Open-ended Phrase Detection

https://github.com/BubblyYi/MMPedestron

공식 코드

When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Dataset

https://github.com/CAIC-AD/YOLOPv2

공식 코드

YOLOPv2: Better, Faster, Stronger for Panoptic Driving Perception

https://github.com/CAMMA-public/ConvLSTM-Surgical-Tool-Tracker

공식 코드

Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos

https://github.com/CAMMA-public/cholect50

공식 코드

CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection

https://github.com/CAPTAIN-WHU/iSAID_Devkit

공식 코드

iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images

https://github.com/CASIA-IVA-Lab/ACSL

공식 코드

Adaptive Class Suppression Loss for Long-Tail Object Detection

https://github.com/CASIA-IVA-Lab/DPT

공식 코드

DPT: Deformable Patch-based Transformer for Visual Recognition

https://github.com/CHENGEZ/Attacking-by-Aligning

공식 코드

Attacking by Aligning: Clean-Label Backdoor Attacks on Object Detection

https://github.com/CPFL/Autoware

공식 코드

LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDAR

https://github.com/CPJKU/cyolo_score_following

공식 코드

Multi-modal Conditional Bounding Box Regression for Music Score Following

https://github.com/CQU-ADHRI-Lab/MI-DETR

공식 코드

MI-DETR: An Object Detection Model with Multi-time Inquiries Mechanism

https://github.com/CQUlearningsystemgroup/YicongPeng

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MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time

https://github.com/CSIPlab/context-aware-attacks

공식 코드

Context-Aware Transfer Attacks for Object Detection

https://github.com/CSL-KU/firesim-nvdla

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Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim

https://github.com/CVMI-Lab/ST3D

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ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

https://github.com/CVMI-Lab/SlotCon

공식 코드

Self-Supervised Visual Representation Learning with Semantic Grouping

https://github.com/Caoang327/vis_det

공식 코드

Inverting and Understanding Object Detectors

https://github.com/Caojunxu/AC-FPN

공식 코드

Attention-guided Context Feature Pyramid Network for Object Detection

https://github.com/CarloSgaravatti/HybridLateCascadeFusion

공식 코드

A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object Detection

https://github.com/Cc-Hy/CMKD

공식 코드

Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection

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