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PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Bottom Up Attention ⭐ 979

Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

Xmodaler ⭐ 929

X-modaler is a versatile and high-performance codebase for cross-modal analytics(e.g., image captioning, video captioning, vision-language pre-training, visual question answering, visual commonsense reasoning, and cross-modal retrieval).

Awesome Computer Vision Resources ⭐ 70

a collection of computer vision projects&tools. 计算机视觉方向项目和工具集合。

[ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.

Multimodal Meta Learn ⭐ 19

Official code repository for "Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning" (published at ICLR 2023).

Crossget ⭐ 13

CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers.

Eye Handicapped Service ⭐ 9

[ X:AI Conference ] 시각장애인을 위한 안내見 서비스

Visual Question Answering System

Related Searches

Python Image Captioning (203)

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