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NVIDIA AI Research Proposes Language Instructed Temporal-Localization Assistant (LITA), which Enables Accurate Temporal Localization Using Video LLMs

[ad_1] Large Language Models (LLMs) have proven their impressive instruction-following capabilities, and they can be a universal interface for various tasks such as text generation, language translation, etc. These models can be extended to multimodal LLMs to process language and other modalities, such…

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MathVerse: An All-Around Visual Math Benchmark Designed for an Equitable and In-Depth Evaluation of Multi-modal Large Language Models (MLLMs)

[ad_1] The performance of multimodal large Language Models (MLLMs) in visual situations has been exceptional, gaining unmatched attention. However, their ability to solve visual math problems must still be fully assessed and comprehended. For this reason, mathematics often presents challenges in understanding complex…

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Researchers from Stanford and Google AI Introduce MELON: An AI Technique that can Determine Object-Centric Camera Poses Entirely from Scratch while Reconstructing the Object in 3D

[ad_1] While humans can easily infer the shape of an object from 2D images, computers struggle to reconstruct accurate 3D models without knowledge of the camera poses. This problem, known as pose inference, is crucial for various applications, like creating 3D models for…

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Revolutionizing Robotic Surgery with Neural Networks: Overcoming Catastrophic Forgetting through Privacy-Preserving Continual Learning in Semantic Segmentation

[ad_1] Deep Neural Networks (DNNs) excel in enhancing surgical precision through semantic segmentation and accurately identifying robotic instruments and tissues. However, they face catastrophic forgetting and a rapid decline in performance on previous tasks when learning new ones, posing challenges in scenarios with…

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CMU Researchers Unveil Groundbreaking AI Method for Camera Pose Estimation: Harnessing Ray Diffusion for Enhanced 3D Reconstruction

[ad_1] The pursuit of high-fidelity 3D representations from sparse images has seen considerable advancements, yet the challenge of accurately determining camera poses remains a significant hurdle. Traditional structure-from-motion methods often falter when faced with limited views, prompting a shift towards learning-based strategies that…

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Revolutionizing Image Quality Assessment: The Introduction of Co-Instruct and MICBench for Enhanced Visual Comparisons

[ad_1] Image Quality Assessment (IQA) is a method that standardizes the evaluation criteria for analyzing different aspects of images, including structural information, visual content, etc. To improve this method, various subjective studies have adopted comparative settings. In recent studies, researchers have explored large…

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