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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/umbc-sanjaylab/favtGAN
공식 코드Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary Labels
https://github.com/umich-bipedlab/optimal_shape_generation
공식 코드https://github.com/umich-bipedlab/optimal_shape_global_pose_estimation
공식 코드https://github.com/uncbiag/ICON
공식 코드https://github.com/unhsaillab/taco
공식 코드https://github.com/unicamp-dl/Lite-T5-Translation
공식 코드Lite Training Strategies for Portuguese-English and English-Portuguese Translation
https://github.com/unicamp-dl/cross-lingual-analysis
공식 코드https://github.com/unicamp-dl/mMARCO
공식 코드mMARCO: A Multilingual Version of the MS MARCO Passage Ranking Dataset
https://github.com/uralik/oversmoothing_rate
공식 코드Characterizing and addressing the issue of oversmoothing in neural autoregressive sequence modeling
https://github.com/urbste/MLPnP_matlab
공식 코드MLPnP - A Real-Time Maximum Likelihood Solution to the Perspective-n-Point Problem
https://github.com/urbste/MLPnP_matlab_toolbox
공식 코드MLPnP - A Real-Time Maximum Likelihood Solution to the Perspective-n-Point Problem
https://github.com/urvashik/knnlm
공식 코드https://github.com/ustlsh/TransPro
공식 코드Vessel-Promoted OCT to OCTA Image Translation by Heuristic Contextual Constraints
https://github.com/utiasSTARS/dpc-net
공식 코드https://github.com/utter-project/SpireLM
공식 코드From TOWER to SPIRE: Adding the Speech Modality to a Text-Only LLM
https://github.com/uulm-mrm/excalibur
공식 코드Globally Optimal Multi-Scale Monocular Hand-Eye Calibration Using Dual Quaternions
https://github.com/uva-dsa/auto_surgical_context2gesture
공식 코드Towards Surgical Context Inference and Translation to Gestures
https://github.com/uva-slpl/embedalign
공식 코드Deep Generative Model for Joint Alignment and Word Representation
https://github.com/uw-cmg/GAN-STEM-Conv2MultiSlice
공식 코드Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation
https://github.com/uw-madison-lee-lab/walip
공식 코드Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment
https://github.com/valdelch/b_cnns
공식 코드SO(2) and O(2) Equivariance in Image Recognition with Bessel-Convolutional Neural Networks
https://github.com/vania-mendonca/MTOL
공식 코드https://github.com/vania-mendonca/Onception
공식 코드Onception: Active Learning with Expert Advice for Real World Machine Translation
https://github.com/varungumma/fairseq
공식 코드https://github.com/vegesm/depthpose
공식 코드Absolute Human Pose Estimation with Depth Prediction Network
https://github.com/verashira/TSPNet
공식 코드TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
https://github.com/vernadankers/mt_idioms
공식 코드Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation
https://github.com/veronicium/cmtrans
공식 코드Data Augmentation for Code Translation with Comparable Corpora and Multiple References
https://github.com/vicmak/Exploiting-BiLSTM-for-Proper-Word-Choice
공식 코드Choosing the Right Word: Using Bidirectional LSTM Tagger for Writing Support Systems
https://github.com/vict0rsch/LiSS
공식 코드Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation
https://github.com/victordibia/data2vis
공식 코드https://github.com/victorwz/zs-nmt-dae
공식 코드Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables
https://github.com/vietai/ViPubmed
공식 코드Enriching Biomedical Knowledge for Low-resource Language Through Large-Scale Translation
https://github.com/vietai/mTet
공식 코드https://github.com/vinairesearch/phomt
공식 코드PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.