https://github.com/ActiveVisionLab/NeFeS
공식 코드Neural Refinement for Absolute Pose Regression with Feature Synthesis
Papers with Code 아카이브
regression
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ActiveVisionLab/direct-posenet
공식 코드Direct-PoseNet: Absolute Pose Regression with Photometric Consistency
https://github.com/Alan-D-Chen/CDIoU-CDIoUloss
공식 코드Control Distance IoU and Control Distance IoU Loss Function for Better Bounding Box Regression
https://github.com/AleksandrIvchenko/QoE-assesment
공식 코드Study on the Assessment of the Quality of Experience of Streaming Video
https://github.com/AleksandrIvchenko/QoE-models
공식 코드Study on the Assessment of the Quality of Experience of Streaming Video
https://github.com/AlexImmer/marglik
공식 코드Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
https://github.com/Ali-Mahzarnia/MFSGrp
공식 코드Multivariate functional group sparse regression: functional predictor selection
https://github.com/AllanSCosta/occam-net
공식 코드OccamNet: A Fast Neural Model for Symbolic Regression at Scale
https://github.com/AlvinZhuyx/camera_pose_representation
공식 코드https://github.com/AmBarry/hidetify
공식 코드https://github.com/Ambrosys/glyph
공식 코드https://github.com/AndReGeist/gp_squared
공식 코드Learning Constrained Dynamics with Gauss Principle adhering Gaussian Processes
https://github.com/ArnoutDevos/RegressionNet
공식 코드Regression Networks for Meta-Learning Few-Shot Classification
https://github.com/Arstanley/fakenews_pscore_match
공식 코드Improving Generalizability of Fake News Detection Methods using Propensity Score Matching
https://github.com/Arthur151/ROMP
공식 코드https://github.com/Arthur151/Relative_Human
공식 코드Putting People in their Place: Monocular Regression of 3D People in Depth
https://github.com/AssafRab/RETCO
공식 코드https://github.com/AvivNavon/MrRCE
공식 코드Capturing Between-Tasks Covariance and Similarities Using Multivariate Linear Mixed Models
https://github.com/BBVA/UMAL
공식 코드Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians
https://github.com/BFZD233/TranScene
공식 코드Multi-Label Stereo Matching for Transparent Scene Depth Estimation
https://github.com/Baran-phys/DynamicFormer
공식 코드https://github.com/BinaLab/ice-thickness-regression
공식 코드Regression Networks For Calculating Englacial Layer Thickness
https://github.com/Binwen6/CS182_PROJECT_2025
공식 코드https://github.com/BioIntelligence-Lab/CT-Embedding-Bias
공식 코드https://github.com/Blei-Lab/lda-bump-cpp
공식 코드https://github.com/Blunde1/aGTBoost
공식 코드An information criterion for automatic gradient tree boosting
https://github.com/BoChenYS/satellite-pose-estimation
공식 코드Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinement
https://github.com/BorealisAI/ranksim-imbalanced-regression
공식 코드RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
https://github.com/BorgwardtLab/graphkernels-review
공식 코드https://github.com/CAMP-eXplain-AI/CheXplain-IBA
공식 코드https://github.com/CCaribe9/HQR-WACI
공식 코드https://github.com/CORE-Robotics-Lab/SSRR
공식 코드Learning from Suboptimal Demonstration via Self-Supervised Reward Regression
https://github.com/CPJKU/cyolo_score_following
공식 코드Multi-modal Conditional Bounding Box Regression for Music Score Following
https://github.com/CPS-research-group/dtsemnet
공식 코드https://github.com/CausalML/LatentConfounderBalancing
공식 코드Policy Evaluation with Latent Confounders via Optimal Balance
https://github.com/ChangWeiTan/TSRegression
공식 코드Monash University, UEA, UCR Time Series Extrinsic Regression Archive
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.