Papers with Code 아카이브
2D Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/NathanUA/BASNet
공식 코드Boundary-Aware Segmentation Network for Mobile and Web Applications
https://github.com/NathanUA/U-2-Net
공식 코드U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
https://github.com/NatiOfir/SuperPixelFusion
공식 코드Multispectral image fusion based on super pixel segmentation
https://github.com/Natlem/M-HTCN
공식 코드Incremental Multi-Target Domain Adaptation for Object Detection with Efficient Domain Transfer
https://github.com/NesterukSergey/segmentation_image_augmentation
공식 코드Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-Case
https://github.com/NeurAI-Lab/UniNet
공식 코드https://github.com/NeuralSec/Daedalus-attack
공식 코드Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples
https://github.com/NeuromorphicComputing/S-TEC
공식 코드https://github.com/Nightmare-n/UniPAD
공식 코드UniPAD: A Universal Pre-training Paradigm for Autonomous Driving
https://github.com/OIPLab-DUT/CoNet
공식 코드Accurate RGB-D Salient Object Detection via Collaborative Learning
https://github.com/OPIXray-author/OPIXray
공식 코드https://github.com/OUCVisionGroup/TISC-Net
공식 코드https://github.com/OVAD-Benchmark/ovad-bechmark-code
공식 코드https://github.com/OfficialBishal/GeomMaskAttack
공식 코드https://github.com/Oleffa/LeagueAI
공식 코드https://github.com/OliverRensu/GLSTR
공식 코드Unifying Global-Local Representations in Salient Object Detection with Transformer
https://github.com/OpenBMB/AgentCPM-GUI
공식 코드AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning
https://github.com/OpenDriveLab/DetAny3D
공식 코드https://github.com/OpenGVLab/M3I-Pretraining
공식 코드Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information
https://github.com/OpenGVLab/PonderV2
공식 코드PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm
https://github.com/OpenRobotLab/Grounded_3D-LLM
공식 코드https://github.com/OpenSpaceAI/Nesie
공식 코드Not Every Side Is Equal: Localization Uncertainty Estimation for Semi-Supervised 3D Object Detection
https://github.com/Owen-Liuyuxuan/visualDet3D
공식 코드Ground-aware Monocular 3D Object Detection for Autonomous Driving
https://github.com/Ozzyz/carla-data-export
공식 코드https://github.com/PJLallen/InstanceSAM2Eval
공식 코드Evaluation Study on SAM 2 for Class-agnostic Instance-level Segmentation
https://github.com/PKUbahuangliuhe/CBNet
공식 코드CBNet: A Novel Composite Backbone Network Architecture for Object Detection
https://github.com/PPOLYpubki/RD3D
공식 코드RGB-D Salient Object Detection via 3D Convolutional Neural Networks
https://github.com/PSCLab-ASU/LW-RetinaNet
공식 코드https://github.com/PaddlePaddle/Paddle
공식 코드PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detector
https://github.com/PaddlePaddle/Paddle3D
공식 코드CAPE: Camera View Position Embedding for Multi-View 3D Object Detection
https://github.com/PaddlePaddle/PaddleClas
공식 코드HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network
https://github.com/PaddlePaddle/PaddleDetection
공식 코드PP-YOLO: An Effective and Efficient Implementation of Object Detector
https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/semi_det/arsl
공식 코드Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection
https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/semi_det/semi_detr
공식 코드Semi-DETR: Semi-Supervised Object Detection with Detection Transformers
https://github.com/PanoAsh/ASOD60K
공식 코드ASOD60K: An Audio-Induced Salient Object Detection Dataset for Panoramic Videos
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.