Papers with Code 아카이브
Image Retrieval
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Image Retrieval is a fundamental and long-standing computer vision task that involves finding images similar to a given query from a large database. It is often considered a form of fine-grained, instance-level classification. The task is integral to image recognition alongside classification and cross-modal retrieval. By leveraging visual similarity and other criteria, image retrieval enables users to efficiently discover relevant images, making it a crucial tool in applications such as search and recommendation.
Extending CLIP for Category-to-image Retrieval in E-commerce
<span style="color:grey; opacity: 0.6">( Image credit: DELF )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/interestingzhuo/pnp_loss
공식 코드https://github.com/interestingzhuo/pnploss
공식 코드https://github.com/irvingmeng/securevector
공식 코드Towards Privacy-Preserving, Real-Time and Lossless Feature Matching
https://github.com/ivanaer/g-universal-clip
공식 코드General Image Descriptors for Open World Image Retrieval using ViT CLIP
https://github.com/j-mahowald/clip-loc-maps
공식 코드Integrating Visual and Textual Inputs for Searching Large-Scale Map Collections with CLIP
https://github.com/j-min/clip-caption-reward
공식 코드https://github.com/jac99/minkloc3dv2
공식 코드Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Training
https://github.com/jacobluber/pathologysearchcomparison
공식 코드https://github.com/jakekrogh/3d-clip-for-brain-mri
공식 코드https://github.com/jakhac/csmae
공식 코드Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing
https://github.com/janesjanes/sketchy
공식 코드https://github.com/jasonppy/fast-vgs-family
공식 코드https://github.com/jasonustc/caffe-multigpu
공식 코드Transform-Invariant Convolutional Neural Networks for Image Classification and Search
https://github.com/jdhao/deep_firearm
공식 코드DeepFirearm: Learning Discriminative Feature Representation for Fine-grained Firearm Retrieval
https://github.com/jenicek/mdir
공식 코드No Fear of the Dark: Image Retrieval under Varying Illumination Conditions
https://github.com/jerryxu0129/hhf
공식 코드HHF: Hashing-guided Hinge Function for Deep Hashing Retrieval
https://github.com/jerryxu0129/hyp2-loss
공식 코드HyP$^2$ Loss: Beyond Hypersphere Metric Space for Multi-label Image Retrieval
https://github.com/jiawangbai/DHTA-master
공식 코드https://github.com/jiforcen/co-occurrence
공식 코드Co-occurrence of deep convolutional features for image search
https://github.com/jinwon-ko/slcd
공식 코드https://github.com/jinyugy21/adv-stickers_rhde
공식 코드Adversarial Sticker: A Stealthy Attack Method in the Physical World
https://github.com/jjmachan/DeepHash
공식 코드https://github.com/jmorlana/dran
공식 코드Reuse your features: unifying retrieval and feature-metric alignment
https://github.com/joez17/chatsearch
공식 코드ChatSearch: a Dataset and a Generative Retrieval Model for General Conversational Image Retrieval
https://github.com/joisino/clear
공식 코드https://github.com/joisino/tiara
공식 코드https://github.com/joniali/evaluating-fairness-discriminative-fms
공식 코드Evaluating the Fairness of Discriminative Foundation Models in Computer Vision
https://github.com/joshengels/rangefilteredann
공식 코드https://github.com/jspenmar/DejaVu_Features
공식 코드Same Features, Different Day: Weakly Supervised Feature Learning for Seasonal Invariance
https://github.com/kakaobrain/noc
공식 코드Noise-aware Learning from Web-crawled Image-Text Data for Image Captioning
https://github.com/kamwoh/concepthash
공식 코드ConceptHash: Interpretable Fine-Grained Hashing via Concept Discovery
https://github.com/kamwoh/sdc
공식 코드Unsupervised Hashing with Similarity Distribution Calibration
https://github.com/kanchen-usc/amc_att
공식 코드AMC: Attention guided Multi-modal Correlation Learning for Image Search
https://github.com/kaz-k/sketch-based-medical-image-retrieval
공식 코드https://github.com/keio-smilab24/relax-former
공식 코드Open-Vocabulary Mobile Manipulation Based on Double Relaxed Contrastive Learning with Dense Labeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.