https://github.com/sajjjadayobi/CLIPfa
Learning Transferable Visual Models From Natural Language Supervision
Papers with Code 아카이브
Benchmarking
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/salaniz/pycocoevalcap
https://github.com/salanueva/UniVSE
Evaluating Multimodal Representations on Visual Semantic Textual Similarity
https://github.com/salesforce/pb-ovd
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/salesforceairesearch/agentlite
BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents
https://github.com/salt-nlp/mic
The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems
https://github.com/sandeepreddy06/fashion-mnist
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/sathishkumark27/mmdetection-icevision
https://github.com/sberbank-ai/ru-clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/scottjiao/Dynamic-selftraining-GCN
Effective Stabilized Self-Training on Few-Labeled Graph Data
https://github.com/scriddie/varsortability
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
https://github.com/securade/hub
https://github.com/semitable/robotic-warehouse
Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks
https://github.com/servicenow/workarena
https://github.com/seung-lab/znn-release
https://github.com/sfujim/BCQ
https://github.com/shamim-hussain/egt
https://github.com/shao-chi/ImageCaption
https://github.com/shaoshitong/NICO
NICO++: Towards Better Benchmarking for Domain Generalization
https://github.com/shengcailiao/QAConv
Is Synthetic Dataset Reliable for Benchmarking Generalizable Person Re-Identification?
https://github.com/shijiel2/cleverhans
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
https://github.com/shinya7y/UniverseNet
https://github.com/shivammehta25/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/shkarupa-alex/tfclip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/showlab/data-centric.vlp
Beyond neural scaling laws: beating power law scaling via data pruning
https://github.com/showlab/datacentric.vlp
Beyond neural scaling laws: beating power law scaling via data pruning
https://github.com/shunk031/simple-aesthetics-predictor
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/sicara/easy-few-shot-learning
https://github.com/silist/mmdet_dev
https://github.com/simsimiSION/pymarl-algorithm-extension-via-starcraft
https://github.com/sincerass/mvlpt
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/sisl/event-driven-rllab
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/sisl/gail-driver
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/sithu31296/simple-object-tracking
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/skylerlinn/understanding-the-ranking-loss
BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
https://github.com/smurthy2020/fashion
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.