Official PyTorch implementation of GroupViT: Semantic Segmentation Emerges from Text Supervision, CVPR 2022.
#自然语言处理#Offline semantic Text-to-Image and Image-to-Image search on Android powered by quantized state-of-the-art vision-language pretrained CLIP model and ONNX Runtime inference engine
#Awesome#The Paper List of Large Multi-Modality Model (Perception, Generation, Unification), Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insigh...
[AAAI2021] The code of “Similarity Reasoning and Filtration for Image-Text Matching”
Code for "Learning the Best Pooling Strategy for Visual Semantic Embedding", CVPR 2021 (Oral)
Code for journal paper "Learning Dual Semantic Relations with Graph Attention for Image-Text Matching", TCSVT, 2020.
#计算机科学#Extended COCO Validation (ECCV) Caption dataset (ECCV 2022)
Official implementation and dataset for the NAACL 2024 paper "ComCLIP: Training-Free Compositional Image and Text Matching"
A non-JIT version implementation / replication of CLIP of OpenAI in pytorch
Easy wrapper for inserting LoRA layers in CLIP.
[TIP2023] The code of “Plug-and-Play Regulators for Image-Text Matching”
#计算机科学#Implementation of the "Learn No to Say Yes Better" paper.
Code implementation of paper "SEMScene: Semantic-Consistency Enhanced Multi-Level Scene Graph Matching for Image-Text Retrieval".
#计算机科学#[ICML 2024] Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
Noise of Web (NoW) is a challenging noisy correspondence learning (NCL) benchmark containing 100K image-text pairs for robust image-text matching/retrieval models.
Text Query based Traffic Video Event Retrieval with Global-Local Fusion Embedding
#搜索#A dead-simple image search / retrieval and image-text matching system for Bangla using CLIP
CLIP (Contrastive Language–Image Pre-training) for Bangla.
[TIP2024] The code of “Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text Matching”
Cross-modal Retrieval using Transformer Encoder Reasoning Networks (TERN). With use of Metric Learning and FAISS for fast similarity search on GPU