https://github.com/fjssharpsword/ASH
공식 코드Attention-based Saliency Hashing for Ophthalmic Image Retrieval
Papers with Code 아카이브
Image Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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/fjssharpsword/ATH
공식 코드Deep Triplet Hashing Network for Case-based Medical Image Retrieval
https://github.com/flagai-open/flagai
공식 코드AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities
https://github.com/flagopen/flagembedding
공식 코드VISTA: Visualized Text Embedding For Universal Multi-Modal Retrieval
https://github.com/flipkart-incubator/fk-visual-search
공식 코드Deep Learning based Large Scale Visual Recommendation and Search for E-Commerce
https://github.com/fra31/perceptual-metrics
공식 코드Adversarially Robust CLIP Models Can Induce Better (Robust) Perceptual Metrics
https://github.com/fuxianghuang1/PWCF
공식 코드Probability Weighted Compact Feature for Domain Adaptive Retrieval
https://github.com/fuxianghuang1/dwc
공식 코드https://github.com/fyang93/diffusion
공식 코드Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing
https://github.com/ga1i13o/divide-and-classify
공식 코드Divide&Classify: Fine-Grained Classification for City-Wide Visual Place Recognition
https://github.com/gaoshuang98/cvcities
공식 코드CV-Cities: Advancing Cross-View Geo-Localization in Global Cities
https://github.com/gbarbarani/MorseDet
공식 코드Scale-Free Image Keypoints Using Differentiable Persistent Homology
https://github.com/gbc8181/TISLF
공식 코드https://github.com/gchrupala/symbolic-bias
공식 코드Symbolic inductive bias for visually grounded learning of spoken language
https://github.com/ghanning/gcsa
공식 코드https://github.com/gimpong/AAAI21-WSDHQ
공식 코드Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval
https://github.com/gimpong/AAAI22-MeCoQ
공식 코드Contrastive Quantization with Code Memory for Unsupervised Image Retrieval
https://github.com/gist-ailab/uoais
공식 코드Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling
https://github.com/gkouros/contrastive-pose-retrieval
공식 코드Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentation
https://github.com/glovo/foodi-ml-dataset
공식 코드FooDI-ML: a large multi-language dataset of food, drinks and groceries images and descriptions
https://github.com/gmberton/auto_vpr
공식 코드EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognition
https://github.com/gmberton/cosplace
공식 코드Rethinking Visual Geo-localization for Large-Scale Applications
https://github.com/gmberton/earthloc
공식 코드EarthLoc: Astronaut Photography Localization by Indexing Earth from Space
https://github.com/gmberton/eigenplaces
공식 코드EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognition
https://github.com/gmberton/image-retrieval
공식 코드https://github.com/gofigure-lanl/figure-segmentation
공식 코드DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding
https://github.com/gofynd/mildnet
공식 코드MILDNet: A Lightweight Single Scaled Deep Ranking Architecture
https://github.com/gombru/LearnFromWebData
공식 코드Learning to Learn from Web Data through Deep Semantic Embeddings
https://github.com/gongzix/lite-mind
공식 코드Lite-Mind: Towards Efficient and Robust Brain Representation Network
https://github.com/goodproj13/DenserNet
공식 코드DenserNet: Weakly Supervised Visual Localization Using Multi-scale Feature Aggregation
https://github.com/google-deepmind/magiclens
공식 코드MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions
https://github.com/google-research-datasets/Objectron
공식 코드Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations
https://github.com/google-research-datasets/wit
공식 코드WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
https://github.com/google-research/composed_image_retrieval
공식 코드Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval
https://github.com/google-research/google-research
공식 코드Yes, we CANN: Constrained Approximate Nearest Neighbors for local feature-based visual localization
https://github.com/google-research/tabnas
공식 코드TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.