Image-text matching

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 102 papers with code (188 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
  28 Nov 2017 20 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation.
• BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
  28 Jan 2022 9 repositories listed
  Furthermore, performance improvement has been largely achieved by scaling up the dataset with noisy image-text pairs collected from the web, which is a suboptimal source of supervision.
• VinVL: Revisiting Visual Representations in Vision-Language Models
  2 Jan 2021 7 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  In our experiments we feed the visual features generated by the new object detection model into a Transformer-based VL fusion model \oscar \cite{li2020oscar}, and utilize an improved approach \short\ to pre-train the VL…
• UNITER: UNiversal Image-TExt Representation Learning
  25 Sep 2019 7 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)
  Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i.
• Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
  16 Jul 2021 6 repositories listed Syntology ran 3 of 5 samples · 2 unverified · 3 pointer-only (licence)
  Most existing methods employ a transformer-based multimodal encoder to jointly model visual tokens (region-based image features) and word tokens.
• Stacked Cross Attention for Image-Text Matching
  21 Mar 2018 6 repositories listed Syntology ran 7 of 16 samples · 9 unverified · 1 pointer-only (licence)
  Prior work either simply aggregates the similarity of all possible pairs of regions and words without attending differentially to more and less important words or regions, or uses a multi-step attentional process to…
• Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
  13 Apr 2020 4 repositories listed Syntology ran 11 of 23 samples · 12 unverified
  Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks.
• Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations
  6 May 2023 3 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  In this paper, we present an end-to-end framework Structure-CLIP, which integrates Scene Graph Knowledge (SGK) to enhance multi-modal structured representations.
• VL-BERT: Pre-training of Generic Visual-Linguistic Representations
  22 Aug 2019 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We introduce a new pre-trainable generic representation for visual-linguistic tasks, called Visual-Linguistic BERT (VL-BERT for short).
• Negative Pre-aware for Noisy Cross-modal Matching
  10 Dec 2023 2 repositories listed
  Since clean samples are easier distinguished by GMM with increasing noise, the memory bank can still maintain high quality at a high noise ratio.
• A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
  24 Jul 2023 2 repositories listed
  This paper aims to provide a comprehensive survey of cutting-edge research in prompt engineering on three types of vision-language models: multimodal-to-text generation models (e.
• A Differentiable Semantic Metric Approximation in Probabilistic Embedding for Cross-Modal Retrieval
  6 Dec 2022 2 repositories listed
  To verify the effectiveness of our approach, extensive experiments are conducted on MS-COCO, CUB Captions, and Flickr30K, which are commonly used in cross-modal retrieval.
• Self-supervised vision-language pretraining for Medical visual question answering
  24 Nov 2022 2 repositories listed Syntology ran 6 of 10 samples · 4 unverified
  Medical image visual question answering (VQA) is a task to answer clinical questions, given a radiographic image, which is a challenging problem that requires a model to integrate both vision and language information.
• Dissecting Deep Metric Learning Losses for Image-Text Retrieval
  21 Oct 2022 2 repositories listed
  In the event that the gradients are not integrable to a valid loss function, we implement our proposed objectives such that they would directly operate in the gradient space instead of on the losses in the embedding…
• ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO
  7 Apr 2022 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  Image-Text matching (ITM) is a common task for evaluating the quality of Vision and Language (VL) models.
• Universal Weighting Metric Learning for Cross-Modal Matching
  7 Oct 2020 2 repositories listed Syntology ran 3 of 11 samples · 8 unverified
  Furthermore, we introduce a new polynomial loss under the universal weighting framework, which defines a weight function for the positive and negative informative pairs respectively.
• Visual Semantic Reasoning for Image-Text Matching
  6 Sep 2019 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  It outperforms the current best method by 6.
• Matching Images and Text with Multi-modal Tensor Fusion and Re-ranking
  12 Aug 2019 2 repositories listed
  We propose a novel framework that achieves remarkable matching performance with acceptable model complexity.
• Dual Attention Networks for Multimodal Reasoning and Matching
  2 Nov 2016 2 repositories listed
  We propose Dual Attention Networks (DANs) which jointly leverage visual and textual attention mechanisms to capture fine-grained interplay between vision and language.
• Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models
  10 Jun 2025 1 repository listed
  ALTA achieves superior performance in vision-language matching tasks like retrieval and zero-shot classification by adapting the pretrained vision model from masked record modeling.
• Aligning Information Capacity Between Vision and Language via Dense-to-Sparse Feature Distillation for Image-Text Matching
  19 Mar 2025 1 repository listed
  Enabling Visual Semantic Models to effectively handle multi-view description matching has been a longstanding challenge.
• CLIP is Strong Enough to Fight Back: Test-time Counterattacks towards Zero-shot Adversarial Robustness of CLIP
  5 Mar 2025 1 repository listed Syntology ran 2 of 4 samples · 2 unverified · 4 pointer-only (licence)
  Our paradigm is simple and training-free, providing the first method to defend CLIP from adversarial attacks at test time, which is orthogonal to existing methods aiming to boost zero-shot adversarial robustness of CLIP.
• IteRPrimE: Zero-shot Referring Image Segmentation with Iterative Grad-CAM Refinement and Primary Word Emphasis
  2 Mar 2025 1 repository listed
  To address these challenges, we propose IteRPrimE (Iterative Grad-CAM Refinement and Primary word Emphasis), which leverages a saliency heatmap through Grad-CAM from a Vision-Language Pre-trained (VLP) model for…
• CLIP Under the Microscope: A Fine-Grained Analysis of Multi-Object Representation
  27 Feb 2025 1 repository listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  Contrastive Language-Image Pre-training (CLIP) models excel in zero-shot classification, yet face challenges in complex multi-object scenarios.
• ReCon: Enhancing True Correspondence Discrimination through Relation Consistency for Robust Noisy Correspondence Learning
  27 Feb 2025 1 repository listed Syntology ran 3 of 5 samples · 2 unverified
  To address this problem, we propose a general Relation Consistency learning framework, namely ReCon, to accurately discriminate the true correspondences among the multimodal data and thus effectively mitigate the…
• FiLo++: Zero-/Few-Shot Anomaly Detection by Fused Fine-Grained Descriptions and Deformable Localization
  17 Jan 2025 1 repository listed
  However, their handcrafted generic descriptions fail to capture the diverse range of anomalies that may emerge in different objects, and simple patch-level image-text matching often struggles to localize anomalous…
• Evaluating Attribute Comprehension in Large Vision-Language Models
  25 Aug 2024 1 repository listed
  Currently, large vision-language models have gained promising progress on many downstream tasks.
• Image-text matching for large-scale book collections
  29 Jul 2024 1 repository listed
  We show that both the Hungarian Matching and the proposed BERT-based model outperform a fuzzy string matching baseline, and we highlight inherent limitations of the matching algorithms as the target increases in size,…
• UGNCL: Uncertainty-Guided Noisy Correspondence Learning for Efficient Cross-Modal Matching
  11 Jul 2024 1 repository listed
  Cross-modal matching has recently gained significant popularity to facilitate retrieval across multi-modal data, and existing works are highly relied on an implicit assumption that the training data pairs are perfectly…
• Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model
  18 Jun 2024 1 repository listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
  For efficient adaptation, we treat the CLIP model as a black box and leverage the extracted features to obtain visual and textual prototypes for prediction.

Syntology lines on 16 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.