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Zero-shot Image Retrieval

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Showing 1–29 of 29 papers

TitleStatusHype
Chinese CLIP: Contrastive Vision-Language Pretraining in ChineseCode5
AltCLIP: Altering the Language Encoder in CLIP for Extended Language CapabilitiesCode4
Cross-lingual and Multilingual CLIPCode2
FLAVA: A Foundational Language And Vision Alignment ModelCode1
Context-I2W: Mapping Images to Context-dependent Words for Accurate Zero-Shot Composed Image RetrievalCode1
FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph ParsingCode1
FETA: Towards Specializing Foundation Models for Expert Task ApplicationsCode1
General Image Descriptors for Open World Image Retrieval using ViT CLIPCode1
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic TasksCode1
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image RetrievalCode1
CCMB: A Large-scale Chinese Cross-modal BenchmarkCode1
Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering—0
Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval—0
Learning with Succinct Common Representation Based on Wyner's Common Information—0
Zero-Shot Hashing via Transferring Supervised Knowledge—0
Piecewise-Linear Manifolds for Deep Metric Learning—0
CLIP-PING: Boosting Lightweight Vision-Language Models with Proximus Intrinsic Neighbors Guidance—0
Attribute-Modulated Generative Meta Learning for Zero-Shot Classification—0
Curriculum Learning for Data-Efficient Vision-Language Alignment—0
Attribute-Guided Network for Cross-Modal Zero-Shot Hashing—0
Full-attention based Neural Architecture Search using Context Auto-regression—0
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training—0
Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval—0
Visual Representation Learning with Self-Supervised Attention for Low-Label High-data RegimeCode0
ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-trainingCode0
Revisiting CLIP: Efficient Alignment of 3D MRI and Tabular Data using Domain-Specific Foundation ModelsCode0
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training BenchmarkCode0
Decoupling the Role of Data, Attention, and Losses in Multimodal TransformersCode0
M2-Encoder: Advancing Bilingual Image-Text Understanding by Large-scale Efficient PretrainingCode0
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