The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
Manzano combines visual understanding and text-to-image generation, while significantly reducing performance or quality trade-offs.
Support image generation in a resolution of 512x512. Improve the multimodal understanding capabilities of purely discrete Show-o. Improve the performance on the GenEval benchmark. Explore the impact ...
This code implements MMTraCE, a multimodal learning framework for traffic accident prediction and causal estimation. We propose a modeling framework that integrates visual encoders with graph neural ...
ABSTRACT: This study proposes a multimodal AI model for classifying Vietnamese digital learning materials by integrating three key information sources: text content, image and graphic features, and ...
Abstract: Existing reinforcement learning based natural language vehicle video clip retrieval methods are limited by the use of shallow networks and inefficient state representations. We propose a ...
Abstract: Music exists in various modalities, such as score images, symbolic scores, MIDI, and audio. Translations between such modalities are established as core tasks of music information retrieval, ...
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Transformer encoder architecture explained simply
We break down the Encoder architecture in Transformers, layer by layer! If you've ever wondered how models like BERT and GPT process text, this is your ultimate guide. We look at the entire design of ...
According to DeepLearning.AI, researchers have introduced Sample-Efficient Modality Integration (SEMI), a framework that enables any pretrained encoder—covering images, audio, video, sensors, and ...
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