https://github.com/ZPDu/Boosting-Object-Detection-with-Zero-Shot-Day-Night-Domain-Adaptation
공식 코드Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation
Papers with Code 아카이브
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ZRandomize/MatrixVT
공식 코드MatrixVT: Efficient Multi-Camera to BEV Transformation for 3D Perception
https://github.com/ZZUTK/SRNTT
공식 코드https://github.com/Ze-Yang/Context-Transformer
공식 코드Context-Transformer: Tackling Object Confusion for Few-Shot Detection
https://github.com/ZeHuiGong/AFSM
공식 코드Towards Better Object Detection in Scale Variation with Adaptive Feature Selection
https://github.com/Zengyi-Qin/MonoGRNet
공식 코드MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization
https://github.com/Zengyi-Qin/Weakly-Supervised-3D-Object-Detection
공식 코드https://github.com/Zeqiang-Lai/HSI-RefSR
공식 코드Hyperspectral Image Super Resolution with Real Unaligned RGB Guidance
https://github.com/ZhangAoCanada/RADDet
공식 코드RADDet: Range-Azimuth-Doppler based Radar Object Detection for Dynamic Road Users
https://github.com/ZhangGongjie/Meta-DETR
공식 코드Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation Exploitation
https://github.com/ZhangLi-CS/GCP_Optimization
공식 코드What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
https://github.com/Zhao-Tian-yi/RSDet
공식 코드Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection
https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation
공식 코드Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/ZhendongWang6/Uformer
공식 코드Uformer: A General U-Shaped Transformer for Image Restoration
https://github.com/Zheng222/IDN-Caffe
공식 코드Fast and Accurate Single Image Super-Resolution via Information Distillation Network
https://github.com/Zheng222/IMDN
공식 코드Lightweight Image Super-Resolution with Information Multi-distillation Network
https://github.com/Zheng222/PPON
공식 코드Progressive Perception-Oriented Network for Single Image Super-Resolution
https://github.com/Zhengbo-Zhang/ITKD
공식 코드https://github.com/ZhengyuLiang24/LFT
공식 코드https://github.com/ZhgLiu/GDD
공식 코드https://github.com/ZhihuaLiuEd/SoTA-Brain-Tumor-Segmentation
공식 코드https://github.com/ZhouYiiFeng/CDSR
공식 코드Joint Learning Content and Degradation Aware Feature for Blind Super-Resolution
https://github.com/Zhourobotics/Query-3DGS-LLM
공식 코드Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D Gaussian
https://github.com/ZhuHaoranEIS/DN-TOD
공식 코드Robust Tiny Object Detection in Aerial Images amidst Label Noise
https://github.com/ZhuKeven/MOBOSR
공식 코드Perceptual-Distortion Balanced Image Super-Resolution is a Multi-Objective Optimization Problem
https://github.com/Zifei-Zhao/OBBDetection
공식 코드https://github.com/Ziwei89/FBOD-BSPL
공식 코드https://github.com/ZiweiWangTHU/BiDet
공식 코드https://github.com/Zizzzzzzz/SMamba_AAAI2025
공식 코드https://github.com/Zyun-Y/BiconNets
공식 코드BiconNet: An Edge-preserved Connectivity-based Approach for Salient Object Detection
https://github.com/Zzh-tju/CIoU
공식 코드https://github.com/Zzh-tju/DIoU
공식 코드Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
https://github.com/a-nau/CubeRefine-R-CNN
공식 코드Parcel3D: Shape Reconstruction from Single RGB Images for Applications in Transportation Logistics
https://github.com/a-nau/synthetic-dataset-generation
공식 코드Scrape, Cut, Paste and Learn: Automated Dataset Generation Applied to Parcel Logistics
https://github.com/a11to1n3/alerttrap-dataset
공식 코드https://github.com/aamir-mustafa/super-resolution-adversarial-defense
공식 코드Image Super-Resolution as a Defense Against Adversarial Attacks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.