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Image-text Retrieval

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Showing 201–225 of 248 papers

TitleStatusHype
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning—0
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training—0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
Uni-Mlip: Unified Self-supervision for Medical Vision Language Pre-training—0
UNITER: Learning UNiversal Image-TExt Representations—0
UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation—0
Variance-Aware Loss Scheduling for Multimodal Alignment in Low-Data Settings—0
ViLEM: Visual-Language Error Modeling for Image-Text Retrieval—0
VL-BEiT: Generative Vision-Language Pretraining—0
VLMAE: Vision-Language Masked Autoencoder—0
VL-Match: Enhancing Vision-Language Pretraining with Token-Level and Instance-Level Matching—0
Webly Supervised Joint Embedding for Cross-Modal Image-Text Retrieval—0
Webly Supervised Joint Embedding for Cross-Modal lmage-Text Retrieval—0
XGPT: Cross-modal Generative Pre-Training for Image Captioning—0
Toward Automatic Relevance Judgment using Vision--Language Models for Image--Text Retrieval Evaluation—0
Re-Imagen: Retrieval-Augmented Text-to-Image Generator—0
Object-Aware Query Perturbation for Cross-Modal Image-Text RetrievalCode0
Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences for Image-Text RetrievalCode0
GSSF: Generalized Structural Sparse Function for Deep Cross-modal Metric LearningCode0
NAPReg: Nouns As Proxies Regularization for Semantically Aware Cross-Modal EmbeddingsCode0
VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language ModelsCode0
MultiWay-Adapater: Adapting large-scale multi-modal models for scalable image-text retrievalCode0
Reversed in Time: A Novel Temporal-Emphasized Benchmark for Cross-Modal Video-Text RetrievalCode0
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training BenchmarkCode0
Embracing Language Inclusivity and Diversity in CLIP through Continual Language LearningCode0
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