Concerns with enabling computers to interpret and understand visual inputs, such as images and videos.
The study introduces two frameworks, the Progressive Multi-task Anti-noise Learning (PMAL) and Progressive Multi-task Distilling (PMD), to tackle the intra-class variation issue in Fine-grained Vehicle Recognition (FGVR) caused by image…
Continue readingThe study presents the Open-World Mobile Manipulation System. This system enables robots to interact with articulated objects such as doors, cabinets, and refrigerators in unstructured environments like homes. The robot…
Continue readingThis article presents a novel methodology named Multimodal Pathway which aims to improve transformers using irrelevant data from other modalities. For instance, an ImageNet model can be improved with audio…
Continue readingThe research focuses on understanding human emotions, particularly fear, in virtual reality (VR) environments. This understanding is crucial in the development of immersive games, scene development, and next-generation human-computer interaction…
Continue readingThis article presents a new method for multiview clustering (MVC) via contrastive learning, called CCEC. MVC is a process that groups data samples into clusters by synthesizing information across multiple…
Continue readingThe study tackles the issues in Automated Model Evaluation (AutoEval), such as overconfidence and high computational cost. It introduces a novel measure, Meta-Distribution Energy (MDE), to enhance the AutoEval framework’s…
Continue readingThe article introduces Dream360, a framework developed to generate diverse, high-fidelity, and high-resolution panoramas from user-selected viewpoints. This technology considers the spherical properties of 360 images, providing a more immersive…
Continue readingThe article, ‘The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology’, analyzes the social practices involved in the measurement and validation of motion…
Continue readingThis study presents an AI-based system for evaluating bee health, using a combination of visual and audio signals. The system’s core is an Attention-based Multimodal Neural Network (AMNN), which focuses…
Continue readingThe article by Anish Lakkapragada, Amol Khanna, Edward Raff, and Nathan Inkawhich discusses the importance of detecting when data is outside the expected input distribution in machine learning. It presents…
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