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2D Classification
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Oleffa/LeagueAI
공식 코드https://github.com/OliverRensu/GLSTR
공식 코드Unifying Global-Local Representations in Salient Object Detection with Transformer
https://github.com/OmarSZamzam/PixelShuffler
공식 코드PixelShuffler: A Simple Image Translation Through Pixel Rearrangement
https://github.com/OndrejTexler/Few-Shot-Patch-Based-Training
공식 코드Interactive Video Stylization Using Few-Shot Patch-Based Training
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/OpenImagingLab/PSF-Estimation
공식 코드A Physics-Informed Blur Learning Framework for Imaging Systems
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/PKU-TANGENT/SciDTB
공식 코드SciDTB: Discourse Dependency TreeBank for Scientific Abstracts
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/PaddlePaddle/PaddleGAN
공식 코드Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer
https://github.com/PaddlePaddle/PaddleHub
공식 코드Parameter-Free Style Projection for Arbitrary Style Transfer
https://github.com/PaddlePaddle/Research
공식 코드Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer
https://github.com/PanoAsh/ASOD60K
공식 코드ASOD60K: An Audio-Induced Salient Object Detection Dataset for Panoramic Videos
https://github.com/PanoAsh/F-360iSOD
공식 코드A Fixation-based 360° Benchmark Dataset for Salient Object Detection
https://github.com/PanoAsh/SA-Net
공식 코드Learning Synergistic Attention for Light Field Salient Object Detection
https://github.com/PanoAsh/SHD360
공식 코드SHD360: A Benchmark Dataset for Salient Human Detection in 360° Videos
https://github.com/Panorama-Bill/F-360iSOD
공식 코드A Fixation-based 360° Benchmark Dataset for Salient Object Detection
https://github.com/ParallelDots/generic-sku-detection-benchmark
공식 코드Benchmark for Generic Product Detection: A Low Data Baseline for Dense Object Detection
https://github.com/ParkLabML/Dirichlet_Pruning
공식 코드https://github.com/Pealing/DFFT
공식 코드https://github.com/PeizeSun/OneNet
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.