https://github.com/naver/kapture
공식 코드Robust Image Retrieval-based Visual Localization using Kapture
Papers with Code 아카이브
Image Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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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/naver/kapture-localization
공식 코드Robust Image Retrieval-based Visual Localization using Kapture
https://github.com/navervision/compodiff
공식 코드CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion
https://github.com/navervision/lincir
공식 코드Language-only Efficient Training of Zero-shot Composed Image Retrieval
https://github.com/navervision/proxy-synthesis
공식 코드Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning
https://github.com/nec-n-sogi/msdpp
공식 코드https://github.com/netease-media/csce-net
공식 코드Cross-Scale Context Extracted Hashing for Fine-Grained Image Binary Encoding
https://github.com/ngzhili/syntable
공식 코드https://github.com/nickhaidos/scenir-icml2025
공식 코드SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
https://github.com/nikosefth/freedom
공식 코드Composed Image Retrieval for Training-Free Domain Conversion
https://github.com/njust-vipgroup/semicon
공식 코드SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image Retrieval
https://github.com/nle-ml/mmkb
공식 코드Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
https://github.com/noahsark/parameterefficient-dml
공식 코드https://github.com/nopperl/clip_arxiv_pmc
공식 코드https://github.com/ntu-icg/fm-planner
공식 코드FM-Planner: Foundation Model Guided Path Planning for Autonomous Drone Navigation
https://github.com/nvlabs/palavra
공식 코드"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
https://github.com/nvlabs/pervlbenchmark
공식 코드"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
https://github.com/ofa-sys/chinese-clip
공식 코드Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese
https://github.com/om-ai-lab/rs5m
공식 코드https://github.com/onlinehuazai/evit
공식 코드EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud Computing
https://github.com/openai/evals
공식 코드https://github.com/opengvlab/internvl
공식 코드InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
https://github.com/openmatch/univl-dr
공식 코드https://github.com/oravus/DeltaDescriptors
공식 코드Delta Descriptors: Change-Based Place Representation for Robust Visual Localization
https://github.com/oravus/seqNet
공식 코드SeqNet: Learning Descriptors for Sequence-based Hierarchical Place Recognition
https://github.com/osimeoni/DSM
공식 코드https://github.com/oulu-imeds/adatriplet
공식 코드https://github.com/paranioar/gssf
공식 코드GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric Learning
https://github.com/paranioar/rcar
공식 코드https://github.com/patchadversarialattacks/patchadversarialattacks
공식 코드Physical Passive Patch Adversarial Attacks on Visual Odometry Systems
https://github.com/paulalbert31/sncf
공식 코드https://github.com/paulaonta/blind-valm
공식 코드Improving the Efficiency of Visually Augmented Language Models
https://github.com/pavelsuma/ames
공식 코드AMES: Asymmetric and Memory-Efficient Similarity Estimation for Instance-level Retrieval
https://github.com/pavelsuma/raml
공식 코드Large-to-small Image Resolution Asymmetry in Deep Metric Learning
https://github.com/pectinid16/IDHN
공식 코드Improved Deep Hashing with Soft Pairwise Similarity for Multi-label Image Retrieval
https://github.com/pengfei-luo/ImageScope
공식 코드ImageScope: Unifying Language-Guided Image Retrieval via Large Multimodal Model Collective Reasoning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.