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VEnhancer: A Generative Space-Time Enhancement Method for Video Generation

Recent advancements in video generation have been driven by large models trained on extensive datasets, employing techniques like adding layers to existing models and joint training. Some approaches use multi-stage processes, combining base models with frame interpolation and super-resolution. Video Super-Resolution (VSR) enhances low-resolution videos, with newer techniques using varied degradation models to better mimic…

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Theia: A Robot Vision Foundation Model that Simultaneously Distills Off-the-Shelf VFMs such as CLIP, DINOv2, and ViT

Visual understanding is the abstracting of high-dimensional visual signals like images and videos. Many problems are involved in this process, ranging from depth prediction and vision-language correspondence to classification and object grounding, which include tasks defined along spatial and temporal axes and tasks defined along coarse to fine granularity, like object grounding. In light of…

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Productionizing a RAG App. Adding evaluation, automated data… | by Ed Izaguirre | Aug, 2024

Adding evaluation, automated data pulling, and other improvements. From Film Search to Rosebud 🌹. Image from Unsplash.Table of Contents Introduction Offline Evaluation Online Evaluation Automated Data Pulling with Prefect Summary Relevant Links A few months ago, I released the Film Search app, a Retrieval-Augmented Generation (RAG) application designed to recommend films based on user queries.…

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Redefining Accuracy in Metrological Instruments

Industries like aviation engineering, pharmaceutics and automotive manufacturing are beginning to rely on artificial intelligence for metrological instrument calibration, valuing it for its unparalleled accuracy and efficiency. How will this technology reshape conventional practices? AI’s Role in Metrological Instrument Calibration It shouldn’t be surprising that AI has applications in metrology — the science of…

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Revolutionising Visual-Language Understanding: VILA 2’s Self-Augmentation and Specialist Knowledge Integration

The field of language models has seen remarkable progress, driven by transformers and scaling efforts. OpenAI’s GPT series demonstrated the power of increasing parameters and high-quality data. Innovations like Transformer-XL expanded context windows, while models such as Mistral, Falcon, Yi, DeepSeek, DBRX, and Gemini pushed capabilities further. Visual language models (VLMs) have also advanced rapidly.…

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AI achieves silver-medal standard solving International Mathematical Olympiad problems

Acknowledgements We thank the International Mathematical Olympiad organization for their support. AlphaProof development was led by Thomas Hubert, Rishi Mehta and Laurent Sartran; AlphaGeometry 2 and natural language reasoning efforts were led by Thang Luong. AlphaProof was developed with key contributions from Hussain Masoom, Aja Huang, Miklós Z. Horváth, Tom Zahavy, Vivek Veeriah, Eric Wieser,…

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