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/miccunifi/cross-the-gap
공식 코드Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality Inversion
https://github.com/miccunifi/searle
공식 코드https://github.com/michaeltian108/ca-tride
공식 코드Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrieval
https://github.com/michalsr/regions
공식 코드https://github.com/microsoft/AirSim-Drone-Racing-VAE-Imitation
공식 코드Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations
https://github.com/microsoft/Oscar
공식 코드Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
https://github.com/microsoft/uicaption
공식 코드https://github.com/microsoft/unilm/tree/master/vlmo
공식 코드VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts
https://github.com/mida-group/crossmodal_imgretrieval
공식 코드Cross-Modality Sub-Image Retrieval using Contrastive Multimodal Image Representations
https://github.com/mikwieczorek/centroids-reid
공식 코드A Strong Baseline for Fashion Retrieval with Person Re-Identification Models
https://github.com/milkyfun0/ERVD
공식 코드ERVD: An Efficient and Robust ViT-Based Distillation Framework for Remote Sensing Image Retrieval
https://github.com/mingu6/ProbFiltersVPR
공식 코드Probabilistic Visual Place Recognition for Hierarchical Localization
https://github.com/miriull/multimodal_absa_elbphilharmonie
공식 코드Retrieving Users' Opinions on Social Media with Multimodal Aspect-Based Sentiment Analysis
https://github.com/mischad/beyondfid
공식 코드https://github.com/mkirchhof/probabilistic_contrastive_learning
공식 코드Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs
https://github.com/mlmed/torchxrayvision
공식 코드TorchXRayVision: A library of chest X-ray datasets and models
https://github.com/mohwald/gandtr
공식 코드Dark Side Augmentation: Generating Diverse Night Examples for Metric Learning
https://github.com/morrisfl/unifex
공식 코드Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval
https://github.com/mpatacchiola/self-supervised-relational-reasoning
공식 코드Self-Supervised Relational Reasoning for Representation Learning
https://github.com/mpskex/Minimizing-Mutual-Information
공식 코드Shuffle and Learn: Minimizing Mutual Information for Unsupervised Hashing
https://github.com/mrazhou/seta
공식 코드https://github.com/mrcgndr/plant_cataloging_workflow
공식 코드https://github.com/msracver/Deep-Exemplar-based-Colorization
공식 코드https://github.com/multimodal-interpretability/nnn
공식 코드Nearest Neighbor Normalization Improves Multimodal Retrieval
https://github.com/mvp18/ttt-ucdr
공식 코드https://github.com/mvrl/context-cir
공식 코드ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval
https://github.com/mzhang367/dcwh
공식 코드Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-wise Loss
https://github.com/mzhang367/hpdh
공식 코드Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval
https://github.com/mzhang367/opqn
공식 코드Orthonormal Product Quantization Network for Scalable Face Image Retrieval
https://github.com/nainanijatinz/zero-search
공식 코드ZeroSearch: Local Image Search from Text with Zero Shot Learning
https://github.com/nainye/radiomicsretrieval
공식 코드RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
https://github.com/nashory/rtic-gcn-pytorch
공식 코드RTIC: Residual Learning for Text and Image Composition using Graph Convolutional Network
https://github.com/naver/artemis
공식 코드ARTEMIS: Attention-based Retrieval with Text-Explicit Matching and Implicit Similarity
https://github.com/naver/cgd
공식 코드Combination of Multiple Global Descriptors for Image Retrieval
https://github.com/naver/fire
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.