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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jacksonchen1998/Empowering-NLG
공식 코드Empowering NLG: Offline Reinforcement Learning for Informal Summarization in Online Domains
https://github.com/jacky121298/wlst
공식 코드https://github.com/jacobdanovitch/Trouble-With-The-Curve
공식 코드Trouble with the Curve: Predicting Future MLB Players Using Scouting Reports
https://github.com/jacobdanovitch/jdnlp
공식 코드Linking Social Media Posts to News with Siamese Transformers
https://github.com/jacobgil/pytorch-grad-cam
공식 코드KPCA-CAM: Visual Explainability of Deep Computer Vision Models using Kernel PCA
https://github.com/jacobhenningsson95/synmfg_code
공식 코드https://github.com/jacobi93/alpha-iou
공식 코드Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
https://github.com/jacobyuan7/ocn-hoi-benchmark
공식 코드Detecting Human-Object Interactions with Object-Guided Cross-Modal Calibrated Semantics
https://github.com/jacobyuan7/rlipv2
공식 코드RLIPv2: Fast Scaling of Relational Language-Image Pre-training
https://github.com/jaehakim97/sr4ir
공식 코드Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss
https://github.com/jaeill/CVPR23-VNE
공식 코드VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution
https://github.com/jakesnell/prototypical-networks
공식 코드https://github.com/jakezhaojb/ARAE
공식 코드https://github.com/jalalilabucla/phycv
공식 코드VEViD: Vision Enhancement via Virtual diffraction and coherent Detection
https://github.com/james128333/HarDNet-MSEG
공식 코드https://github.com/jamie-cheung/artbank
공식 코드ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank
https://github.com/jamie-cheung/lsast
공식 코드https://github.com/jammer345/SL-CycleGAN-Blind-Motion-Deblurring-in-Cycles-using-Sparse-Learning
공식 코드SL-CycleGAN: Blind Motion Deblurring in Cycles using Sparse Learning
https://github.com/janetzhong/saved-you-a-click-cs224n
공식 코드https://github.com/janghyuncho/ecm-loss
공식 코드https://github.com/jankowskichristopher/red-teaming-segment-anything-model
공식 코드https://github.com/janmarcelkezmann/metadetect3d
공식 코드LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds
https://github.com/jannctu/FINED
공식 코드https://github.com/jaraxxus-me/airdet
공식 코드AirDet: Few-Shot Detection without Fine-tuning for Autonomous Exploration
https://github.com/jarchv/solverip
공식 코드Generative Flows as a General Purpose Solution for Inverse Problems
https://github.com/jarek-pawlowski/microbial-dataset-generation
공식 코드Generation of microbial colonies dataset with deep learning style transfer
https://github.com/jarintotiondin/ziragroundingdino
공식 코드Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection
https://github.com/jaryp/adaptivesemantictokencommunication
공식 코드Adaptive Semantic Token Communication for Transformer-based Edge Inference
https://github.com/jasmine-tjy/semantic-based-point-cloud-tasks
공식 코드Implicit Guidance and Explicit Representation of Semantic Information in Points Cloud: A Survey
https://github.com/jason-lim26/dipex
공식 코드DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection
https://github.com/jasonyzhang/ners
공식 코드NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild
https://github.com/jaychempan/ETS
공식 코드https://github.com/jaychempan/LAE-DINO
공식 코드Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community
https://github.com/jayded/evidence-inference
공식 코드Inferring Which Medical Treatments Work from Reports of Clinical Trials
https://github.com/jayoungkim408/sos
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.