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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MCoT-RE: Multi-Faceted Chain-of-Thought and Re-Ranking for Training-Free Zero-Shot Composed Image Retrieval
FAR-Net: Multi-Stage Fusion Network with Enhanced Semantic Alignment and Adaptive Reconciliation for Composed Image Retrieval
RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features
MS-DPPs: Multi-Source Determinantal Point Processes for Contextual Diversity Refinement of Composite Attributes in Text to Image Retrieval
Orchestrator-Agent Trust: A Modular Agentic AI Visual Classification System with Trust-Aware Orchestration and RAG-Based Reasoning
Automatic Synthesis of High-Quality Triplet Data for Composed Image Retrieval
An analysis of vision-language models for fabric retrieval
Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model
Mask-aware Text-to-Image Retrieval: Referring Expression Segmentation Meets Cross-modal Retrieval
On the Burstiness of Faces in Set
Referring Expression Instance Retrieval and A Strong End-to-End Baseline
Class Agnostic Instance-level Descriptor for Visual Instance Search
Fine-grained Image Retrieval via Dual-Vision Adaptation
Hierarchical Multi-Positive Contrastive Learning for Patent Image Retrieval
A Semantically-Aware Relevance Measure for Content-Based Medical Image Retrieval Evaluation
Hierarchical Image Matching for UAV Absolute Visual Localization via Semantic and Structural Constraints
Improving Personalized Search with Regularized Low-Rank Parameter Updates
Hidden Bias in the Machine: Stereotypes in Text-to-Image Models
Quantization-based Bounds on the Wasserstein Metric
SORCE: Small Object Retrieval in Complex Environments
Sketch Down the FLOPs: Towards Efficient Networks for Human Sketch
Fast Feature Matching of UAV Images via Matrix Band Reduction-based GPU Data Schedule
ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval
FM-Planner: Foundation Model Guided Path Planning for Autonomous Drone Navigation
MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval
One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP
Can Visual Encoder Learn to See Arrows?
Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval
Visualized Text-to-Image Retrieval
TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP
DetailFusion: A Dual-branch Framework with Detail Enhancement for Composed Image Retrieval
DART$^3$: Leveraging Distance for Test Time Adaptation in Person Re-Identification
IA-T2I: Internet-Augmented Text-to-Image Generation
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.