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Researchers from the University of Tubingen Propose SIGNeRF: A Novel AI Approach for Fast and Controllable NeRF Scene Editing and Scene-Integrated Object Generation

Neural Radiance Fields (NeRF) have revolutionized how everyone approaches 3D content creation, offering unparalleled realism in virtual and augmented reality applications. However, editing these scenes has been complex and cumbersome, often requiring intricate processes and yielding inconsistent results. The current landscape of NeRF scene editing involves a range of methods that, while effective in certain…

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Moving Earth, Word, and Concept. Distance as a measure of difference | by Danielle Boccelli | Jan, 2024

Photo by Nadine Shaabana on UnsplashDistance as a measure of difference This article discusses three measures of distance: (1) the Earth Mover’s Distance (EMD; Rubner et al., 1998); (2) the Word Mover’s Distance (WMD; Kusner et al., 2015); and (3) the Concept Mover’s Distance (CMD; Stoltz & Taylor, 2019). These measures build on one another…

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This AI Paper from Victoria University of Wellington and NVIDIA Unveils TrailBlazer: A Novel AI Approach to Simplify Video Synthesis Using Bounding Boxes

Advancements in generative models for text-to-image (T2I) have been dramatic. Recently, text-to-video (T2V) systems have made significant strides, enabling the automatic generation of videos based on textual prompt descriptions. One primary challenge in video synthesis is the extensive memory and training data required. Methods based on the pre-trained Stable Diffusion (SD) model have been proposed…

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Improving language models by retrieving from trillions of tokens

In recent years, significant performance gains in autoregressive language modeling have been achieved by increasing the number of parameters in Transformer models. This has led to a tremendous increase in training energy cost and resulted in a generation of dense “Large Language Models” (LLMs) with 100+ billion parameters. Simultaneously, large datasets containing trillions of words…

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