As we adopt it in a 3D SSD, there are new challenges in reliability so that reprogramming should be applied with constraints. To the best of our knowledge, our work is the first to test reprogramming on a product 3D NAND SSD to verify its feasibility, and derive its constraints.
We propose a new page writing sequence approach for 3D NAND flash SSDs called SFWS. We conduct experimental analysis on a commercial off-the-shelf (COTS) 32-layer 3D NAND chip that supports multi-level-cell (MLC) storage to contrast our SFWS approach with the traditional LFWS.
Zero-shot 3D semantic segmentation approaches require a set of semantic labels as an input together with the 3D shape. Our problem is more difficult than traditional co-segmentation, because the two input shapes may not share the same region names.
We start with Section 2 where we present methods to acquire 3D facial data for model building. We then describe in Section 3 the various approaches to model the 3D shape and facial appearance. In Section 4, we discuss the methods to generate a 2D image from our 3D model using computer graphics.
We first discussed the relationship between 2D and 3D visualisations with surfaces and spaces, followed by describing the possible tasks that these transformations can fulfil when transitioning between four main states: single-view 2D, single-view 3D, multi-view 2D, and multi-view 3D.
Immersive authoring provides an intuitive medium for users to create 3D scenes via direct manipulation in Virtual Reality (VR). Recent advances in generative AI have enabled the automatic creation of realistic 3D layouts.
Our pipeline consists of decoupled steps, allowing users to test various prompt ideas and preview the stylized 3D result before proceeding to the NeRF fine-tuning stage. We demonstrate that our method can transfer diverse artistic styles to real-world 3D scenes with competitive quality.
Vision-based error detection in 3D printing can be categorised into global and local approaches. Global error detection is crucial in identifying various issues, such as geometric accuracy, thermal deformation or surface defects.
While vision-based approaches for 3D human pose estimation have shown great promise, they require subjects to be within the camera's field of view, limiting their practicability for mobile and on-the-go applications.
Based on the 3D blob scene representation, we propose an online and autoregressive 3D-consistent freeview image sequence generation pipeline that generates cross-view coherent images for a given 3D scene conditioned on camera poses and depth inputs.
