https://github.com/Chaolei98/FreeZAD
CoCa: Contrastive Captioners are Image-Text Foundation Models
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 11
- 보존된 평가 기록
- 19
A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ChengXu1995/test
Learning Discriminative 3D Shape Representations by View Discerning Networks
https://github.com/ChienYiChi/kaggle-panda-challenge
NetVLAD: CNN architecture for weakly supervised place recognition
https://github.com/ChrisWu1997/2D-Motion-Retargeting
Learning Character-Agnostic Motion for Motion Retargeting in 2D
https://github.com/ChuuyaZZZ/6787-Final-project
https://github.com/Cloud-CV/vilbert-multi-task
12-in-1: Multi-Task Vision and Language Representation Learning
https://github.com/Cloud-CV/visual-chatbot
https://github.com/Code-kunkun/LamRA
LamRA: Large Multimodal Model as Your Advanced Retrieval Assistant
https://github.com/ColumbiaDVMM/ColumbiaImageSearch
DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks
https://github.com/CompVis/metric-learning-divide-and-conquer
https://github.com/Confusezius/ICCV2019_MIC
MIC: Mining Interclass Characteristics for Improved Metric Learning
https://github.com/CorentinBT/Decoder
Learning to compress and search visual data in large-scale systems
https://github.com/D-Roberts/multilingual-nli-ECIR2021
https://github.com/D-X-Y/GDAS
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
https://github.com/D-X-Y/NAS-Projects
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
https://github.com/DJAlexJ/LRCN-for-Video-Regression
Long-term Recurrent Convolutional Networks for Visual Recognition and Description
https://github.com/Dahny/IN4325-Core-IR-Project
https://github.com/Dai7Igarashi/Anomaly-Detection
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images
https://github.com/DataCanvasIO/DeepTables
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
https://github.com/DataTerminatorX/Keyword-BERT
https://github.com/Deepu1992/VideoClassification
Long-term Recurrent Convolutional Networks for Visual Recognition and Description
https://github.com/Demonhesusheng/Reid
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/DeryanurT/Final_Project
https://github.com/DevHyung/dialogue_cl
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/DianaSHV/lemniscate_edit
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination
https://github.com/Dou-Yu-xuan/pykinship
Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge
https://github.com/Doyosae/Deep-Complex-Networks
https://github.com/DreadPiratePsyopus/Pytorch-yolo-phoc
https://github.com/DreamingRaven/Nemesyst
Deep Learning based Recommender System: A Survey and New Perspectives
https://github.com/DuanYiqun/Auto-ReID-Fast
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification
https://github.com/Ducvoccer/mildnet
https://github.com/ESBigeard/paper_graph
HybridCite: A Hybrid Model for Context-Aware Citation Recommendation
https://github.com/EdoardoBotta/RQ-VAE-Recommender
https://github.com/EdwardLin2014/CNN-with-IBM-for-Singing-Voice-Separation
https://github.com/Efficient-Scalable-Machine-Learning/event-ssm
https://github.com/EmanueleC/DRMM_repro
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.